qualitative research interview setting

How to conduct qualitative interviews (tips and best practices)

Last updated

18 May 2023

Reviewed by

Miroslav Damyanov

However, conducting qualitative interviews can be challenging, even for seasoned researchers. Poorly conducted interviews can lead to inaccurate or incomplete data, significantly compromising the validity and reliability of your research findings.

When planning to conduct qualitative interviews, you must adequately prepare yourself to get the most out of your data. Fortunately, there are specific tips and best practices that can help you conduct qualitative interviews effectively.

What is a qualitative interview?

A qualitative interview is a research technique used to gather in-depth information about people's experiences, attitudes, beliefs, and perceptions. Unlike a structured questionnaire or survey, a qualitative interview is a flexible, conversational approach that allows the interviewer to delve into the interviewee's responses and explore their insights and experiences.

In a qualitative interview, the researcher typically develops a set of open-ended questions that provide a framework for the conversation. However, the interviewer can also adapt to the interviewee's responses and ask follow-up questions to understand their experiences and views better.

How to conduct interviews in qualitative research

Conducting interviews involves a well-planned and deliberate process to collect accurate and valid data.

Here’s a step-by-step guide on how to conduct interviews in qualitative research, broken down into three stages:

1. Before the interview

The first step in conducting a qualitative interview is determining your research question . This will help you identify the type of participants you need to recruit . Once you have your research question, you can start recruiting participants by identifying potential candidates and contacting them to gauge their interest in participating in the study.

After that, it's time to develop your interview questions. These should be open-ended questions that will elicit detailed responses from participants. You'll also need to get consent from the participants, ideally in writing, to ensure that they understand the purpose of the study and their rights as participants. Finally, choose a comfortable and private location to conduct the interview and prepare the interview guide.

2. During the interview

Start by introducing yourself and explaining the purpose of the study. Establish a rapport by putting the participants at ease and making them feel comfortable. Use the interview guide to ask the questions, but be flexible and ask follow-up questions to gain more insight into the participants' responses.

Take notes during the interview, and ask permission to record the interview for transcription purposes. Be mindful of the time, and cover all the questions in the interview guide.

3. After the interview

Once the interview is over, transcribe the interview if you recorded it. If you took notes, review and organize them to make sure you capture all the important information. Then, analyze the data you collected by identifying common themes and patterns. Use the findings to answer your research question.

Finally, debrief with the participants to thank them for their time, provide feedback on the study, and answer any questions they may have.

What kinds of questions should you ask in a qualitative interview?

Qualitative interviews involve asking questions that encourage participants to share their experiences, opinions, and perspectives on a particular topic. These questions are designed to elicit detailed and nuanced responses rather than simple yes or no answers.

Effective questions in a qualitative interview are generally open-ended and non-leading. They avoid presuppositions or assumptions about the participant's experience and allow them to share their views in their own words.

In customer research , you might ask questions such as:

What motivated you to choose our product/service over our competitors?

How did you first learn about our product/service?

Can you walk me through your experience with our product/service?

What improvements or changes would you suggest for our product/service?

Have you recommended our product/service to others, and if so, why?

The key is to ask questions relevant to the research topic and allow participants to share their experiences meaningfully and informally.

How to determine the right qualitative interview participants

Choosing the right participants for a qualitative interview is a crucial step in ensuring the success and validity of the research . You need to consider several factors to determine the right participants for a qualitative interview. These may include:

Relevant experiences : Participants should have experiences related to the research topic that can provide valuable insights.

Diversity : Aim to include diverse participants to ensure the study's findings are representative and inclusive.

Access : Identify participants who are accessible and willing to participate in the study.

Informed consent : Participants should be fully informed about the study's purpose, methods, and potential risks and benefits and be allowed to provide informed consent.

You can use various recruitment methods, such as posting ads in relevant forums, contacting community organizations or social media groups, or using purposive sampling to identify participants who meet specific criteria.

How to make qualitative interview subjects comfortable

Making participants comfortable during a qualitative interview is essential to obtain rich, detailed data. Participants are more likely to share their experiences openly when they feel at ease and not judged.

Here are some ways to make interview subjects comfortable:

Explain the purpose of the study

Start the interview by explaining the research topic and its importance. The goal is to give participants a sense of what to expect.

Create a comfortable environment

Conduct the interview in a quiet, private space where the participant feels comfortable. Turn off any unnecessary electronics that can create distractions. Ensure your equipment works well ahead of time. Arrive at the interview on time. If you conduct a remote interview, turn on your camera and mute all notetakers and observers.

Build rapport

Greet the participant warmly and introduce yourself. Show interest in their responses and thank them for their time.

Use open-ended questions

Ask questions that encourage participants to elaborate on their thoughts and experiences.

Listen attentively

Resist the urge to multitask . Pay attention to the participant's responses, nod your head, or make supportive comments to show you’re interested in their answers. Avoid interrupting them.

Avoid judgment

Show respect and don't judge the participant's views or experiences. Allow the participant to speak freely without feeling judged or ridiculed.

Offer breaks

If needed, offer breaks during the interview, especially if the topic is sensitive or emotional.

Creating a comfortable environment and establishing rapport with the participant fosters an atmosphere of trust and encourages open communication. This helps participants feel at ease and willing to share their experiences.

How to analyze a qualitative interview

Analyzing a qualitative interview involves a systematic process of examining the data collected to identify patterns, themes, and meanings that emerge from the responses.

Here are some steps on how to analyze a qualitative interview:

1. Transcription

The first step is transcribing the interview into text format to have a written record of the conversation. This step is essential to ensure that you can refer back to the interview data and identify the important aspects of the interview.

2. Data reduction

Once you’ve transcribed the interview, read through it to identify key themes, patterns, and phrases emerging from the data. This process involves reducing the data into more manageable pieces you can easily analyze.

The next step is to code the data by labeling sections of the text with descriptive words or phrases that reflect the data's content. Coding helps identify key themes and patterns from the interview data.

4. Categorization

After coding, you should group the codes into categories based on their similarities. This process helps to identify overarching themes or sub-themes that emerge from the data.

5. Interpretation

You should then interpret the themes and sub-themes by identifying relationships, contradictions, and meanings that emerge from the data. Interpretation involves analyzing the themes in the context of the research question .

6. Comparison

The next step is comparing the data across participants or groups to identify similarities and differences. This step helps to ensure that the findings aren’t just specific to one participant but can be generalized to the wider population.

7. Triangulation

To ensure the findings are valid and reliable, you should use triangulation by comparing the findings with other sources, such as observations or interview data.

8. Synthesis

The final step is synthesizing the findings by summarizing the key themes and presenting them clearly and concisely. This step involves writing a report that presents the findings in a way that is easy to understand, using quotes and examples from the interview data to illustrate the themes.

Tips for transcribing a qualitative interview

Transcribing a qualitative interview is a crucial step in the research process. It involves converting the audio or video recording of the interview into written text.

Here are some tips for transcribing a qualitative interview:

Use transcription software

Transcription software can save time and increase accuracy by automatically transcribing audio or video recordings.

Listen carefully

When manually transcribing, listen carefully to the recording to ensure clarity. Pause and rewind the recording as necessary.

Use appropriate formatting

Use a consistent format for transcribing, such as marking pauses, overlaps, and interruptions. Indicate non-verbal cues such as laughter, sighs, or changes in tone.

Edit for clarity

Edit the transcription to ensure clarity and readability. Use standard grammar and punctuation, correct misspellings, and remove filler words like "um" and "ah."

Proofread and edit

Verify the accuracy of the transcription by listening to the recording again and reviewing the notes taken during the interview.

Use timestamps

Add timestamps to the transcription to reference specific interview sections.

Transcribing a qualitative interview can be time-consuming, but it’s essential to ensure the accuracy of the data collected. Following these tips can produce high-quality transcriptions useful for analysis and reporting.

Why are interview techniques in qualitative research effective?

Unlike quantitative research methods, which rely on numerical data, qualitative research seeks to understand the richness and complexity of human experiences and perspectives.

Interview techniques involve asking open-ended questions that allow participants to express their views and share their stories in their own words. This approach can help researchers to uncover unexpected or surprising insights that may not have been discovered through other research methods.

Interview techniques also allow researchers to establish rapport with participants, creating a comfortable and safe space for them to share their experiences. This can lead to a deeper level of trust and candor, leading to more honest and authentic responses.

What are the weaknesses of qualitative interviews?

Qualitative interviews are an excellent research approach when used properly, but they have their drawbacks.

The weaknesses of qualitative interviews include the following:

Subjectivity and personal biases

Qualitative interviews rely on the researcher's interpretation of the interviewee's responses. The researcher's biases or preconceptions can affect how the questions are framed and how the responses are interpreted, which can influence results.

Small sample size

The sample size in qualitative interviews is often small, which can limit the generalizability of the results to the larger population.

Data quality

The quality of data collected during interviews can be affected by various factors, such as the interviewee's mood, the setting of the interview, and the interviewer's skills and experience.

Socially desirable responses

Interviewees may provide responses that they believe are socially acceptable rather than truthful or genuine.

Conducting qualitative interviews can be expensive, especially if the researcher must travel to different locations to conduct the interviews.

Time-consuming

The data analysis process can be time-consuming and labor-intensive, as researchers need to transcribe and analyze the data manually.

Despite these weaknesses, qualitative interviews remain a valuable research tool . You can take steps to mitigate the impact of these weaknesses by incorporating the perspectives of other researchers or participants in the analysis process, using multiple data sources , and critically analyzing your biases and assumptions.

Mastering the art of qualitative interviews is an essential skill for businesses looking to gain deep insights into their customers' needs , preferences, and behaviors. By following the tips and best practices outlined in this article, you can conduct interviews that provide you with rich data that you can use to make informed decisions about your products, services, and marketing strategies.

Remember that effective communication, active listening, and proper analysis are critical components of successful qualitative interviews. By incorporating these practices into your customer research, you can gain a competitive edge and build stronger customer relationships.

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Interviews in the social sciences

Eleanor Knott ORCID: orcid.org/0000-0002-9131-3939 1 ,
Aliya Hamid Rao ORCID: orcid.org/0000-0003-0674-4206 1 ,
Kate Summers ORCID: orcid.org/0000-0001-9964-0259 1 &
Chana Teeger ORCID: orcid.org/0000-0002-5046-8280 1

Nature Reviews Methods Primers volume 2 , Article number: 73 ( 2022 ) Cite this article

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Interdisciplinary studies

In-depth interviews are a versatile form of qualitative data collection used by researchers across the social sciences. They allow individuals to explain, in their own words, how they understand and interpret the world around them. Interviews represent a deceptively familiar social encounter in which people interact by asking and answering questions. They are, however, a very particular type of conversation, guided by the researcher and used for specific ends. This dynamic introduces a range of methodological, analytical and ethical challenges, for novice researchers in particular. In this Primer, we focus on the stages and challenges of designing and conducting an interview project and analysing data from it, as well as strategies to overcome such challenges.

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Introduction

In-depth interviews are a qualitative research method that follow a deceptively familiar logic of human interaction: they are conversations where people talk with each other, interact and pose and answer questions 1 . An interview is a specific type of interaction in which — usually and predominantly — a researcher asks questions about someone’s life experience, opinions, dreams, fears and hopes and the interview participant answers the questions 1 .

Interviews will often be used as a standalone method or combined with other qualitative methods, such as focus groups or ethnography, or quantitative methods, such as surveys or experiments. Although interviewing is a frequently used method, it should not be viewed as an easy default for qualitative researchers 2 . Interviews are also not suited to answering all qualitative research questions, but instead have specific strengths that should guide whether or not they are deployed in a research project. Whereas ethnography might be better suited to trying to observe what people do, interviews provide a space for extended conversations that allow the researcher insights into how people think and what they believe. Quantitative surveys also give these kinds of insights, but they use pre-determined questions and scales, privileging breadth over depth and often overlooking harder-to-reach participants.

In-depth interviews can take many different shapes and forms, often with more than one participant or researcher. For example, interviews might be highly structured (using an almost survey-like interview guide), entirely unstructured (taking a narrative and free-flowing approach) or semi-structured (using a topic guide ). Researchers might combine these approaches within a single project depending on the purpose of the interview and the characteristics of the participant. Whatever form the interview takes, researchers should be mindful of the dynamics between interviewer and participant and factor these in at all stages of the project.

In this Primer, we focus on the most common type of interview: one researcher taking a semi-structured approach to interviewing one participant using a topic guide. Focusing on how to plan research using interviews, we discuss the necessary stages of data collection. We also discuss the stages and thought-process behind analysing interview material to ensure that the richness and interpretability of interview material is maintained and communicated to readers. The Primer also tracks innovations in interview methods and discusses the developments we expect over the next 5–10 years.

We wrote this Primer as researchers from sociology, social policy and political science. We note our disciplinary background because we acknowledge that there are disciplinary differences in how interviews are approached and understood as a method.

Experimentation

Here we address research design considerations and data collection issues focusing on topic guide construction and other pragmatics of the interview. We also explore issues of ethics and reflexivity that are crucial throughout the research project.

Research design

Participant selection.

Participants can be selected and recruited in various ways for in-depth interview studies. The researcher must first decide what defines the people or social groups being studied. Often, this means moving from an abstract theoretical research question to a more precise empirical one. For example, the researcher might be interested in how people talk about race in contexts of diversity. Empirical settings in which this issue could be studied could include schools, workplaces or adoption agencies. The best research designs should clearly explain why the particular setting was chosen. Often there are both intrinsic and extrinsic reasons for choosing to study a particular group of people at a specific time and place 3 . Intrinsic motivations relate to the fact that the research is focused on an important specific social phenomenon that has been understudied. Extrinsic motivations speak to the broader theoretical research questions and explain why the case at hand is a good one through which to address them empirically.

Next, the researcher needs to decide which types of people they would like to interview. This decision amounts to delineating the inclusion and exclusion criteria for the study. The criteria might be based on demographic variables, like race or gender, but they may also be context-specific, for example, years of experience in an organization. These should be decided based on the research goals. Researchers should be clear about what characteristics would make an individual a candidate for inclusion in the study (and what would exclude them).

The next step is to identify and recruit the study’s sample . Usually, many more people fit the inclusion criteria than can be interviewed. In cases where lists of potential participants are available, the researcher might want to employ stratified sampling , dividing the list by characteristics of interest before sampling.

When there are no lists, researchers will often employ purposive sampling . Many researchers consider purposive sampling the most useful mode for interview-based research since the number of interviews to be conducted is too small to aim to be statistically representative 4 . Instead, the aim is not breadth, via representativeness, but depth via rich insights about a set of participants. In addition to purposive sampling, researchers often use snowball sampling . Both purposive and snowball sampling can be combined with quota sampling . All three types of sampling aim to ensure a variety of perspectives within the confines of a research project. A goal for in-depth interview studies can be to sample for range, being mindful of recruiting a diversity of participants fitting the inclusion criteria.

Study design

The total number of interviews depends on many factors, including the population studied, whether comparisons are to be made and the duration of interviews. Studies that rely on quota sampling where explicit comparisons are made between groups will require a larger number of interviews than studies focused on one group only. Studies where participants are interviewed over several hours, days or even repeatedly across years will tend to have fewer participants than those that entail a one-off engagement.

Researchers often stop interviewing when new interviews confirm findings from earlier interviews with no new or surprising insights (saturation) 4 , 5 , 6 . As a criterion for research design, saturation assumes that data collection and analysis are happening in tandem and that researchers will stop collecting new data once there is no new information emerging from the interviews. This is not always possible. Researchers rarely have time for systematic data analysis during data collection and they often need to specify their sample in funding proposals prior to data collection. As a result, researchers often draw on existing reports of saturation to estimate a sample size prior to data collection. These suggest between 12 and 20 interviews per category of participant (although researchers have reported saturation with samples that are both smaller and larger than this) 7 , 8 , 9 . The idea of saturation has been critiqued by many qualitative researchers because it assumes that meaning inheres in the data, waiting to be discovered — and confirmed — once saturation has been reached 7 . In-depth interview data are often multivalent and can give rise to different interpretations. The important consideration is, therefore, not merely how many participants are interviewed, but whether one’s research design allows for collecting rich and textured data that provide insight into participants’ understandings, accounts, perceptions and interpretations.

Sometimes, researchers will conduct interviews with more than one participant at a time. Researchers should consider the benefits and shortcomings of such an approach. Joint interviews may, for example, give researchers insight into how caregivers agree or debate childrearing decisions. At the same time, they may be less adaptive to exploring aspects of caregiving that participants may not wish to disclose to each other. In other cases, there may be more than one person interviewing each participant, such as when an interpreter is used, and so it is important to consider during the research design phase how this might shape the dynamics of the interview.

Data collection

Semi-structured interviews are typically organized around a topic guide comprised of an ordered set of broad topics (usually 3–5). Each topic includes a set of questions that form the basis of the discussion between the researcher and participant (Fig. 1 ). These topics are organized around key concepts that the researcher has identified (for example, through a close study of prior research, or perhaps through piloting a small, exploratory study) 5 .

a | Elaborated topics the researcher wants to cover in the interview and example questions. b | An example topic arc. Using such an arc, one can think flexibly about the order of topics. Considering the main question for each topic will help to determine the best order for the topics. After conducting some interviews, the researcher can move topics around if a different order seems to make sense.

Topic guide

One common way to structure a topic guide is to start with relatively easy, open-ended questions (Table 1 ). Opening questions should be related to the research topic but broad and easy to answer, so that they help to ease the participant into conversation.

After these broad, opening questions, the topic guide may move into topics that speak more directly to the overarching research question. The interview questions will be accompanied by probes designed to elicit concrete details and examples from the participant (see Table 1 ).

Abstract questions are often easier for participants to answer once they have been asked more concrete questions. In our experience, for example, questions about feelings can be difficult for some participants to answer, but when following probes concerning factual experiences these questions can become less challenging. After the main themes of the topic guide have been covered, the topic guide can move onto closing questions. At this stage, participants often repeat something they have said before, although they may sometimes introduce a new topic.

Interviews are especially well suited to gaining a deeper insight into people’s experiences. Getting these insights largely depends on the participants’ willingness to talk to the researcher. We recommend designing open-ended questions that are more likely to elicit an elaborated response and extended reflection from participants rather than questions that can be answered with yes or no.

Questions should avoid foreclosing the possibility that the participant might disagree with the premise of the question. Take for example the question: “Do you support the new family-friendly policies?” This question minimizes the possibility of the participant disagreeing with the premise of this question, which assumes that the policies are ‘family-friendly’ and asks for a yes or no answer. Instead, asking more broadly how a participant feels about the specific policy being described as ‘family-friendly’ (for example, a work-from-home policy) allows them to express agreement, disagreement or impartiality and, crucially, to explain their reasoning 10 .

For an uninterrupted interview that will last between 90 and 120 minutes, the topic guide should be one to two single-spaced pages with questions and probes. Ideally, the researcher will memorize the topic guide before embarking on the first interview. It is fine to carry a printed-out copy of the topic guide but memorizing the topic guide ahead of the interviews can often make the interviewer feel well prepared in guiding the participant through the interview process.

Although the topic guide helps the researcher stay on track with the broad areas they want to cover, there is no need for the researcher to feel tied down by the topic guide. For instance, if a participant brings up a theme that the researcher intended to discuss later or a point the researcher had not anticipated, the researcher may well decide to follow the lead of the participant. The researcher’s role extends beyond simply stating the questions; it entails listening and responding, making split-second decisions about what line of inquiry to pursue and allowing the interview to proceed in unexpected directions.

Optimizing the interview

The ideal place for an interview will depend on the study and what is feasible for participants. Generally, a place where the participant and researcher can both feel relaxed, where the interview can be uninterrupted and where noise or other distractions are limited is ideal. But this may not always be possible and so the researcher needs to be prepared to adapt their plans within what is feasible (and desirable for participants).

Another key tool for the interview is a recording device (assuming that permission for recording has been given). Recording can be important to capture what the participant says verbatim. Additionally, it can allow the researcher to focus on determining what probes and follow-up questions they want to pursue rather than focusing on taking notes. Sometimes, however, a participant may not allow the researcher to record, or the recording may fail. If the interview is not recorded we suggest that the researcher takes brief notes during the interview, if feasible, and then thoroughly make notes immediately after the interview and try to remember the participant’s facial expressions, gestures and tone of voice. Not having a recording of an interview need not limit the researcher from getting analytical value from it.

As soon as possible after each interview, we recommend that the researcher write a one-page interview memo comprising three key sections. The first section should identify two to three important moments from the interview. What constitutes important is up to the researcher’s discretion 9 . The researcher should note down what happened in these moments, including the participant’s facial expressions, gestures, tone of voice and maybe even the sensory details of their surroundings. This exercise is about capturing ethnographic detail from the interview. The second part of the interview memo is the analytical section with notes on how the interview fits in with previous interviews, for example, where the participant’s responses concur or diverge from other responses. The third part consists of a methodological section where the researcher notes their perception of their relationship with the participant. The interview memo allows the researcher to think critically about their positionality and practice reflexivity — key concepts for an ethical and transparent research practice in qualitative methodology 11 , 12 .

Ethics and reflexivity

All elements of an in-depth interview can raise ethical challenges and concerns. Good ethical practice in interview studies often means going beyond the ethical procedures mandated by institutions 13 . While discussions and requirements of ethics can differ across disciplines, here we focus on the most pertinent considerations for interviews across the research process for an interdisciplinary audience.

Ethical considerations prior to interview

Before conducting interviews, researchers should consider harm minimization, informed consent, anonymity and confidentiality, and reflexivity and positionality. It is important for the researcher to develop their own ethical sensitivities and sensibilities by gaining training in interview and qualitative methods, reading methodological and field-specific texts on interviews and ethics and discussing their research plans with colleagues.

Researchers should map the potential harm to consider how this can be minimized. Primarily, researchers should consider harm from the participants’ perspective (Box 1 ). But, it is also important to consider and plan for potential harm to the researcher, research assistants, gatekeepers, future researchers and members of the wider community 14 . Even the most banal of research topics can potentially pose some form of harm to the participant, researcher and others — and the level of harm is often highly context-dependent. For example, a research project on religion in society might have very different ethical considerations in a democratic versus authoritarian research context because of how openly or not such topics can be discussed and debated 15 .

The researcher should consider how they will obtain and record informed consent (for example, written or oral), based on what makes the most sense for their research project and context 16 . Some institutions might specify how informed consent should be gained. Regardless of how consent is obtained, the participant must be made aware of the form of consent, the intentions and procedures of the interview and potential forms of harm and benefit to the participant or community before the interview commences. Moreover, the participant must agree to be interviewed before the interview commences. If, in addition to interviews, the study contains an ethnographic component, it is worth reading around this topic (see, for example, Murphy and Dingwall 17 ). Informed consent must also be gained for how the interview will be recorded before the interview commences. These practices are important to ensure the participant is contributing on a voluntary basis. It is also important to remind participants that they can withdraw their consent at any time during the interview and for a specified period after the interview (to be decided with the participant). The researcher should indicate that participants can ask for anything shared to be off the record and/or not disseminated.

In terms of anonymity and confidentiality, it is standard practice when conducting interviews to agree not to use (or even collect) participants’ names and personal details that are not pertinent to the study. Anonymizing can often be the safer option for minimizing harm to participants as it is hard to foresee all the consequences of de-anonymizing, even if participants agree. Regardless of what a researcher decides, decisions around anonymity must be agreed with participants during the process of gaining informed consent and respected following the interview.

Although not all ethical challenges can be foreseen or planned for 18 , researchers should think carefully — before the interview — about power dynamics, participant vulnerability, emotional state and interactional dynamics between interviewer and participant, even when discussing low-risk topics. Researchers may then wish to plan for potential ethical issues, for example by preparing a list of relevant organizations to which participants can be signposted. A researcher interviewing a participant about debt, for instance, might prepare in advance a list of debt advice charities, organizations and helplines that could provide further support and advice. It is important to remember that the role of an interviewer is as a researcher rather than as a social worker or counsellor because researchers may not have relevant and requisite training in these other domains.

Box 1 Mapping potential forms of harm

Social: researchers should avoid causing any relational detriment to anyone in the course of interviews, for example, by sharing information with other participants or causing interview participants to be shunned or mistreated by their community as a result of participating.

Economic: researchers should avoid causing financial detriment to anyone, for example, by expecting them to pay for transport to be interviewed or to potentially lose their job as a result of participating.

Physical: researchers should minimize the risk of anyone being exposed to violence as a result of the research both from other individuals or from authorities, including police.

Psychological: researchers should minimize the risk of causing anyone trauma (or re-traumatization) or psychological anguish as a result of the research; this includes not only the participant but importantly the researcher themselves and anyone that might read or analyse the transcripts, should they contain triggering information.

Political: researchers should minimize the risk of anyone being exposed to political detriment as a result of the research, such as retribution.

Professional/reputational: researchers should minimize the potential for reputational damage to anyone connected to the research (this includes ensuring good research practices so that any researchers involved are not harmed reputationally by being involved with the research project).

The task here is not to map exhaustively the potential forms of harm that might pertain to a particular research project (that is the researcher’s job and they should have the expertise most suited to mapping such potential harms relative to the specific project) but to demonstrate the breadth of potential forms of harm.

Ethical considerations post-interview

Researchers should consider how interview data are stored, analysed and disseminated. If participants have been offered anonymity and confidentiality, data should be stored in a way that does not compromise this. For example, researchers should consider removing names and any other unnecessary personal details from interview transcripts, password-protecting and encrypting files and using pseudonyms to label and store all interview data. It is also important to address where interview data are taken (for example, across borders in particular where interview data might be of interest to local authorities) and how this might affect the storage of interview data.

Examining how the researcher will represent participants is a paramount ethical consideration both in the planning stages of the interview study and after it has been conducted. Dissemination strategies also need to consider questions of anonymity and representation. In small communities, even if participants are given pseudonyms, it might be obvious who is being described. Anonymizing not only the names of those participating but also the research context is therefore a standard practice 19 . With particularly sensitive data or insights about the participant, it is worth considering describing participants in a more abstract way rather than as specific individuals. These practices are important both for protecting participants’ anonymity but can also affect the ability of the researcher and others to return ethically to the research context and similar contexts 20 .

Reflexivity and positionality

Reflexivity and positionality mean considering the researcher’s role and assumptions in knowledge production 13 . A key part of reflexivity is considering the power relations between the researcher and participant within the interview setting, as well as how researchers might be perceived by participants. Further, researchers need to consider how their own identities shape the kind of knowledge and assumptions they bring to the interview, including how they approach and ask questions and their analysis of interviews (Box 2 ). Reflexivity is a necessary part of developing ethical sensibility as a researcher by adapting and reflecting on how one engages with participants. Participants should not feel judged, for example, when they share information that researchers might disagree with or find objectionable. How researchers deal with uncomfortable moments or information shared by participants is at their discretion, but they should consider how they will react both ahead of time and in the moment.

Researchers can develop their reflexivity by considering how they themselves would feel being asked these interview questions or represented in this way, and then adapting their practice accordingly. There might be situations where these questions are not appropriate in that they unduly centre the researchers’ experiences and worldview. Nevertheless, these prompts can provide a useful starting point for those beginning their reflexive journey and developing an ethical sensibility.

Reflexivity and ethical sensitivities require active reflection throughout the research process. For example, researchers should take care in interview memos and their notes to consider their assumptions, potential preconceptions, worldviews and own identities prior to and after interviews (Box 2 ). Checking in with assumptions can be a way of making sure that researchers are paying close attention to their own theoretical and analytical biases and revising them in accordance with what they learn through the interviews. Researchers should return to these notes (especially when analysing interview material), to try to unpack their own effects on the research process as well as how participants positioned and engaged with them.

Box 2 Aspects to reflect on reflexively

For reflexive engagement, and understanding the power relations being co-constructed and (re)produced in interviews, it is necessary to reflect, at a minimum, on the following.

Ethnicity, race and nationality, such as how does privilege stemming from race or nationality operate between the researcher, the participant and research context (for example, a researcher from a majority community may be interviewing a member of a minority community)

Gender and sexuality, see above on ethnicity, race and nationality

Social class, and in particular the issue of middle-class bias among researchers when formulating research and interview questions

Economic security/precarity, see above on social class and thinking about the researcher’s relative privilege and the source of biases that stem from this

Educational experiences and privileges, see above

Disciplinary biases, such as how the researcher’s discipline/subfield usually approaches these questions, possibly normalizing certain assumptions that might be contested by participants and in the research context

Political and social values

Lived experiences and other dimensions of ourselves that affect and construct our identity as researchers

In this section, we discuss the next stage of an interview study, namely, analysing the interview data. Data analysis may begin while more data are being collected. Doing so allows early findings to inform the focus of further data collection, as part of an iterative process across the research project. Here, the researcher is ultimately working towards achieving coherence between the data collected and the findings produced to answer successfully the research question(s) they have set.

The two most common methods used to analyse interview material across the social sciences are thematic analysis 21 and discourse analysis 22 . Thematic analysis is a particularly useful and accessible method for those starting out in analysis of qualitative data and interview material as a method of coding data to develop and interpret themes in the data 21 . Discourse analysis is more specialized and focuses on the role of discourse in society by paying close attention to the explicit, implicit and taken-for-granted dimensions of language and power 22 , 23 . Although thematic and discourse analysis are often discussed as separate techniques, in practice researchers might flexibly combine these approaches depending on the object of analysis. For example, those intending to use discourse analysis might first conduct thematic analysis as a way to organize and systematize the data. The object and intention of analysis might differ (for example, developing themes or interrogating language), but the questions facing the researcher (such as whether to take an inductive or deductive approach to analysis) are similar.

Preparing data

Data preparation is an important step in the data analysis process. The researcher should first determine what comprises the corpus of material and in what form it will it be analysed. The former refers to whether, for example, alongside the interviews themselves, analytic memos or observational notes that may have been taken during data collection will also be directly analysed. The latter refers to decisions about how the verbal/audio interview data will be transformed into a written form, making it suitable for processes of data analysis. Typically, interview audio recordings are transcribed to produce a written transcript. It is important to note that the process of transcription is one of transformation. The verbal interview data are transformed into a written transcript through a series of decisions that the researcher must make. The researcher should consider the effect of mishearing what has been said or how choosing to punctuate a sentence in a particular way will affect the final analysis.

Box 3 shows an example transcript excerpt from an interview with a teacher conducted by Teeger as part of her study of history education in post-apartheid South Africa 24 (Box 3 ). Seeing both the questions and the responses means that the reader can contextualize what the participant (Ms Mokoena) has said. Throughout the transcript the researcher has used square brackets, for example to indicate a pause in speech, when Ms Mokoena says “it’s [pause] it’s a difficult topic”. The transcription choice made here means that we see that Ms Mokoena has taken time to pause, perhaps to search for the right words, or perhaps because she has a slight apprehension. Square brackets are also included as an overt act of communication to the reader. When Ms Mokoena says “ja”, the English translation (“yes”) of the word in Afrikaans is placed in square brackets to ensure that the reader can follow the meaning of the speech.

Decisions about what to include when transcribing will be hugely important for the direction and possibilities of analysis. Researchers should decide what they want to capture in the transcript, based on their analytic focus. From a (post)positivist perspective 25 , the researcher may be interested in the manifest content of the interview (such as what is said, not how it is said). In that case, they may choose to transcribe intelligent verbatim . From a constructivist perspective 25 , researchers may choose to record more aspects of speech (including, for example, pauses, repetitions, false starts, talking over one another) so that these features can be analysed. Those working from this perspective argue that to recognize the interactional nature of the interview setting adequately and to avoid misinterpretations, features of interaction (pauses, overlaps between speakers and so on) should be preserved in transcription and therefore in the analysis 10 . Readers interested in learning more should consult Potter and Hepburn’s summary of how to present interaction through transcription of interview data 26 .

The process of analysing semi-structured interviews might be thought of as a generative rather than an extractive enterprise. Findings do not already exist within the interview data to be discovered. Rather, researchers create something new when analysing the data by applying their analytic lens or approach to the transcripts. At a high level, there are options as to what researchers might want to glean from their interview data. They might be interested in themes, whereby they identify patterns of meaning across the dataset 21 . Alternatively, they may focus on discourse(s), looking to identify how language is used to construct meanings and therefore how language reinforces or produces aspects of the social world 27 . Alternatively, they might look at the data to understand narrative or biographical elements 28 .

A further overarching decision to make is the extent to which researchers bring predetermined framings or understandings to bear on their data, or instead begin from the data themselves to generate an analysis. One way of articulating this is the extent to which researchers take a deductive approach or an inductive approach to analysis. One example of a truly inductive approach is grounded theory, whereby the aim of the analysis is to build new theory, beginning with one’s data 6 , 29 . In practice, researchers using thematic and discourse analysis often combine deductive and inductive logics and describe their process instead as iterative (referred to also as an abductive approach ) 30 , 31 . For example, researchers may decide that they will apply a given theoretical framing, or begin with an initial analytic framework, but then refine or develop these once they begin the process of analysis.

Box 3 Excerpt of interview transcript (from Teeger 24 )

Interviewer : Maybe you could just start by talking about what it’s like to teach apartheid history.

Ms Mokoena : It’s a bit challenging. You’ve got to accommodate all the kids in the class. You’ve got to be sensitive to all the racial differences. You want to emphasize the wrongs that were done in the past but you also want to, you know, not to make kids feel like it’s their fault. So you want to use the wrongs of the past to try and unite the kids …

Interviewer : So what kind of things do you do?

Ms Mokoena : Well I normally highlight the fact that people that were struggling were not just the blacks, it was all the races. And I give examples of the people … from all walks of life, all races, and highlight how they suffered as well as a result of apartheid, particularly the whites… . What I noticed, particularly my first year of teaching apartheid, I noticed that the black kids made the others feel responsible for what happened… . I had a lot of fights…. A lot of kids started hating each other because, you know, the others are white and the others were black. And they started saying, “My mother is a domestic worker because she was never allowed an opportunity to get good education.” …

Interviewer : I didn’t see any of that now when I was observing.

Ms Mokoena : … Like I was saying I think that because of the re-emphasis of the fact that, look, everybody did suffer one way or the other, they sort of got to see that it was everybody’s struggle … . They should now get to understand that that’s why we’re called a Rainbow Nation. Not everybody agreed with apartheid and not everybody suffered. Even all the blacks, not all blacks got to feel what the others felt . So ja [yes], it’s [pause] it’s a difficult topic, ja . But I think if you get the kids to understand why we’re teaching apartheid in the first place and you show the involvement of all races in all the different sides , then I think you have managed to teach it properly. So I think because of my inexperience then — that was my first year of teaching history — so I think I — maybe I over-emphasized the suffering of the blacks versus the whites [emphasis added].

Reprinted with permission from ref. 24 , Sage Publications.

From data to codes

Coding data is a key building block shared across many approaches to data analysis. Coding is a way of organizing and describing data, but is also ultimately a way of transforming data to produce analytic insights. The basic practice of coding involves highlighting a segment of text (this may be a sentence, a clause or a longer excerpt) and assigning a label to it. The aim of the label is to communicate some sort of summary of what is in the highlighted piece of text. Coding is an iterative process, whereby researchers read and reread their transcripts, applying and refining their codes, until they have a coding frame (a set of codes) that is applied coherently across the dataset and that captures and communicates the key features of what is contained in the data as it relates to the researchers’ analytic focus.

What one codes for is entirely contingent on the focus of the research project and the choices the researcher makes about the approach to analysis. At first, one might apply descriptive codes, summarizing what is contained in the interviews. It is rarely desirable to stop at this point, however, because coding is a tool to move from describing the data to interpreting the data. Suppose the researcher is pursuing some version of thematic analysis. In that case, it might be that the objects of coding are aspects of reported action, emotions, opinions, norms, relationships, routines, agreement/disagreement and change over time. A discourse analysis might instead code for different types of speech acts, tropes, linguistic or rhetorical devices. Multiple types of code might be generated within the same research project. What is important is that researchers are aware of the choices they are making in terms of what they are coding for. Moreover, through the process of refinement, the aim is to produce a set of discrete codes — in which codes are conceptually distinct, as opposed to overlapping. By using the same codes across the dataset, the researcher can capture commonalities across the interviews. This process of refinement involves relabelling codes and reorganizing how and where they are applied in the dataset.

From coding to analysis and writing

Data analysis is also an iterative process in which researchers move closer to and further away from the data. As they move away from the data, they synthesize their findings, thus honing and articulating their analytic insights. As they move closer to the data, they ground these insights in what is contained in the interviews. The link should not be broken between the data themselves and higher-order conceptual insights or claims being made. Researchers must be able to show evidence for their claims in the data. Figure 2 summarizes this iterative process and suggests the sorts of activities involved at each stage more concretely.

As well as going through steps 1 to 6 in order, the researcher will also go backwards and forwards between stages. Some stages will themselves be a forwards and backwards processing of coding and refining when working across different interview transcripts.

At the stage of synthesizing, there are some common quandaries. When dealing with a dataset consisting of multiple interviews, there will be salient and minority statements across different participants, or consensus or dissent on topics of interest to the researcher. A strength of qualitative interviews is that we can build in these nuances and variations across our data as opposed to aggregating them away. When exploring and reporting data, researchers should be asking how different findings are patterned and which interviews contain which codes, themes or tropes. Researchers should think about how these variations fit within the longer flow of individual interviews and what these variations tell them about the nature of their substantive research interests.

A further consideration is how to approach analysis within and across interview data. Researchers may look at one individual code, to examine the forms it takes across different participants and what they might be able to summarize about this code in the round. Alternatively, they might look at how a code or set of codes pattern across the account of one participant, to understand the code(s) in a more contextualized way. Further analysis might be done according to different sampling characteristics, where researchers group together interviews based on certain demographic characteristics and explore these together.

When it comes to writing up and presenting interview data, key considerations tend to rest on what is often termed transparency. When presenting the findings of an interview-based study, the reader should be able to understand and trace what the stated findings are based upon. This process typically involves describing the analytic process, how key decisions were made and presenting direct excerpts from the data. It is important to account for how the interview was set up and to consider the active part that the researcher has played in generating the data 32 . Quotes from interviews should not be thought of as merely embellishing or adding interest to a final research output. Rather, quotes serve the important function of connecting the reader directly to the underlying data. Quotes, therefore, should be chosen because they provide the reader with the most apt insight into what is being discussed. It is good practice to report not just on what participants said, but also on the questions that were asked to elicit the responses.

Researchers have increasingly used specialist qualitative data analysis software to organize and analyse their interview data, such as NVivo or ATLAS.ti. It is important to remember that such software is a tool for, rather than an approach or technique of, analysis. That said, software also creates a wide range of possibilities in terms of what can be done with the data. As researchers, we should reflect on how the range of possibilities of a given software package might be shaping our analytical choices and whether these are choices that we do indeed want to make.

Applications

This section reviews how and why in-depth interviews have been used by researchers studying gender, education and inequality, nationalism and ethnicity and the welfare state. Although interviews can be employed as a method of data collection in just about any social science topic, the applications below speak directly to the authors’ expertise and cutting-edge areas of research.

When it comes to the broad study of gender, in-depth interviews have been invaluable in shaping our understanding of how gender functions in everyday life. In a study of the US hedge fund industry (an industry dominated by white men), Tobias Neely was interested in understanding the factors that enable white men to prosper in the industry 33 . The study comprised interviews with 45 hedge fund workers and oversampled women of all races and men of colour to capture a range of experiences and beliefs. Tobias Neely found that practices of hiring, grooming and seeding are key to maintaining white men’s dominance in the industry. In terms of hiring, the interviews clarified that white men in charge typically preferred to hire people like themselves, usually from their extended networks. When women were hired, they were usually hired to less lucrative positions. In terms of grooming, Tobias Neely identifies how older and more senior men in the industry who have power and status will select one or several younger men as their protégés, to include in their own elite networks. Finally, in terms of her concept of seeding, Tobias Neely describes how older men who are hedge fund managers provide the seed money (often in the hundreds of millions of dollars) for a hedge fund to men, often their own sons (but not their daughters). These interviews provided an in-depth look into gendered and racialized mechanisms that allow white men to flourish in this industry.

Research by Rao draws on dozens of interviews with men and women who had lost their jobs, some of the participants’ spouses and follow-up interviews with about half the sample approximately 6 months after the initial interview 34 . Rao used interviews to understand the gendered experience and understanding of unemployment. Through these interviews, she found that the very process of losing their jobs meant different things for men and women. Women often saw job loss as being a personal indictment of their professional capabilities. The women interviewed often referenced how years of devaluation in the workplace coloured their interpretation of their job loss. Men, by contrast, were also saddened by their job loss, but they saw it as part and parcel of a weak economy rather than a personal failing. How these varied interpretations occurred was tied to men’s and women’s very different experiences in the workplace. Further, through her analysis of these interviews, Rao also showed how these gendered interpretations had implications for the kinds of jobs men and women sought to pursue after job loss. Whereas men remained tied to participating in full-time paid work, job loss appeared to be a catalyst pushing some of the women to re-evaluate their ties to the labour force.

In a study of workers in the tech industry, Hart used interviews to explain how individuals respond to unwanted and ambiguously sexual interactions 35 . Here, the researcher used interviews to allow participants to describe how these interactions made them feel and act and the logics of how they interpreted, classified and made sense of them 35 . Through her analysis of these interviews, Hart showed that participants engaged in a process she termed “trajectory guarding”, whereby they sought to monitor unwanted and ambiguously sexual interactions to avoid them from escalating. Yet, as Hart’s analysis proficiently demonstrates, these very strategies — which protect these workers sexually — also undermined their workplace advancement.

Drawing on interviews, these studies have helped us to understand better how gendered mechanisms, gendered interpretations and gendered interactions foster gender inequality when it comes to paid work. Methodologically, these studies illuminate the power of interviews to reveal important aspects of social life.

Nationalism and ethnicity

Traditionally, nationalism has been studied from a top-down perspective, through the lens of the state or using historical methods; in other words, in-depth interviews have not been a common way of collecting data to study nationalism. The methodological turn towards everyday nationalism has encouraged more scholars to go to the field and use interviews (and ethnography) to understand nationalism from the bottom up: how people talk about, give meaning, understand, navigate and contest their relation to nation, national identification and nationalism 36 , 37 , 38 , 39 . This turn has also addressed the gap left by those studying national and ethnic identification via quantitative methods, such as surveys.

Surveys can enumerate how individuals ascribe to categorical forms of identification 40 . However, interviews can question the usefulness of such categories and ask whether these categories are reflected, or resisted, by participants in terms of the meanings they give to identification 41 , 42 . Categories often pitch identification as a mutually exclusive choice; but identification might be more complex than such categories allow. For example, some might hybridize these categories or see themselves as moving between and across categories 43 . Hearing how people talk about themselves and their relation to nations, states and ethnicities, therefore, contributes substantially to the study of nationalism and national and ethnic forms of identification.

One particular approach to studying these topics, whether via everyday nationalism or alternatives, is that of using interviews to capture both articulations and narratives of identification, relations to nationalism and the boundaries people construct. For example, interviews can be used to gather self–other narratives by studying how individuals construct I–we–them boundaries 44 , including how participants talk about themselves, who participants include in their various ‘we’ groupings and which and how participants create ‘them’ groupings of others, inserting boundaries between ‘I/we’ and ‘them’. Overall, interviews hold great potential for listening to participants and understanding the nuances of identification and the construction of boundaries from their point of view.

Education and inequality

Scholars of social stratification have long noted that the school system often reproduces existing social inequalities. Carter explains that all schools have both material and sociocultural resources 45 . When children from different backgrounds attend schools with different material resources, their educational and occupational outcomes are likely to vary. Such material resources are relatively easy to measure. They are operationalized as teacher-to-student ratios, access to computers and textbooks and the physical infrastructure of classrooms and playgrounds.

Drawing on Bourdieusian theory 46 , Carter conceptualizes the sociocultural context as the norms, values and dispositions privileged within a social space 45 . Scholars have drawn on interviews with students and teachers (as well as ethnographic observations) to show how schools confer advantages on students from middle-class families, for example, by rewarding their help-seeking behaviours 47 . Focusing on race, researchers have revealed how schools can remain socioculturally white even as they enrol a racially diverse student population. In such contexts, for example, teachers often misrecognize the aesthetic choices made by students of colour, wrongly inferring that these students’ tastes in clothing and music reflect negative orientations to schooling 48 , 49 , 50 . These assessments can result in disparate forms of discipline and may ultimately shape educators’ assessments of students’ academic potential 51 .

Further, teachers and administrators tend to view the appropriate relationship between home and school in ways that resonate with white middle-class parents 52 . These parents are then able to advocate effectively for their children in ways that non-white parents are not 53 . In-depth interviews are particularly good at tapping into these understandings, revealing the mechanisms that confer privilege on certain groups of students and thereby reproduce inequality.

In addition, interviews can shed light on the unequal experiences that young people have within educational institutions, as the views of dominant groups are affirmed while those from disadvantaged backgrounds are delegitimized. For example, Teeger’s interviews with South African high schoolers showed how — because racially charged incidents are often framed as jokes in the broader school culture — Black students often feel compelled to ignore and keep silent about the racism they experience 54 . Interviews revealed that Black students who objected to these supposed jokes were coded by other students as serious or angry. In trying to avoid such labels, these students found themselves unable to challenge the racism they experienced. Interviews give us insight into these dynamics and help us see how young people understand and interpret the messages transmitted in schools — including those that speak to issues of inequality in their local school contexts as well as in society more broadly 24 , 55 .

The welfare state

In-depth interviews have also proved to be an important method for studying various aspects of the welfare state. By welfare state, we mean the social institutions relating to the economic and social wellbeing of a state’s citizens. Notably, using interviews has been useful to look at how policy design features are experienced and play out on the ground. Interviews have often been paired with large-scale surveys to produce mixed-methods study designs, therefore achieving both breadth and depth of insights.

In-depth interviews provide the opportunity to look behind policy assumptions or how policies are designed from the top down, to examine how these play out in the lives of those affected by the policies and whose experiences might otherwise be obscured or ignored. For example, the Welfare Conditionality project used interviews to critique the assumptions that conditionality (such as, the withdrawal of social security benefits if recipients did not perform or meet certain criteria) improved employment outcomes and instead showed that conditionality was harmful to mental health, living standards and had many other negative consequences 56 . Meanwhile, combining datasets from two small-scale interview studies with recipients allowed Summers and Young to critique assumptions around the simplicity that underpinned the design of Universal Credit in 2020, for example, showing that the apparently simple monthly payment design instead burdened recipients with additional money management decisions and responsibilities 57 .

Similarly, the Welfare at a (Social) Distance project used a mixed-methods approach in a large-scale study that combined national surveys with case studies and in-depth interviews to investigate the experience of claiming social security benefits during the COVID-19 pandemic. The interviews allowed researchers to understand in detail any issues experienced by recipients of benefits, such as delays in the process of claiming, managing on a very tight budget and navigating stigma and claiming 58 .

These applications demonstrate the multi-faceted topics and questions for which interviews can be a relevant method for data collection. These applications highlight not only the relevance of interviews, but also emphasize the key added value of interviews, which might be missed by other methods (surveys, in particular). Interviews can expose and question what is taken for granted and directly engage with communities and participants that might otherwise be ignored, obscured or marginalized.

Reproducibility and data deposition

There is a robust, ongoing debate about reproducibility in qualitative research, including interview studies. In some research paradigms, reproducibility can be a way of interrogating the rigour and robustness of research claims, by seeing whether these hold up when the research process is repeated. Some scholars have suggested that although reproducibility may be challenging, researchers can facilitate it by naming the place where the research was conducted, naming participants, sharing interview and fieldwork transcripts (anonymized and de-identified in cases where researchers are not naming people or places) and employing fact-checkers for accuracy 11 , 59 , 60 .

In addition to the ethical concerns of whether de-anonymization is ever feasible or desirable, it is also important to address whether the replicability of interview studies is meaningful. For example, the flexibility of interviews allows for the unexpected and the unforeseen to be incorporated into the scope of the research 61 . However, this flexibility means that we cannot expect reproducibility in the conventional sense, given that different researchers will elicit different types of data from participants. Sharing interview transcripts with other researchers, for instance, downplays the contextual nature of an interview.

Drawing on Bauer and Gaskell, we propose several measures to enhance rigour in qualitative research: transparency, grounding interpretations and aiming for theoretical transferability and significance 62 .

Researchers should be transparent when describing their methodological choices. Transparency means documenting who was interviewed, where and when (without requiring de-anonymization, for example, by documenting their characteristics), as well as the questions they were asked. It means carefully considering who was left out of the interviews and what that could mean for the researcher’s findings. It also means carefully considering who the researcher is and how their identity shaped the research process (integrating and articulating reflexivity into whatever is written up).

Second, researchers should ground their interpretations in the data. Grounding means presenting the evidence upon which the interpretation relies. Quotes and extracts should be extensive enough to allow the reader to evaluate whether the researcher’s interpretations are grounded in the data. At each step, researchers should carefully compare their own explanations and interpretations with alternative explanations. Doing so systematically and frequently allows researchers to become more confident in their claims. Here, researchers should justify the link between data and analysis by using quotes to justify and demonstrate the analytical point, while making sure the analytical point offers an interpretation of quotes (Box 4 ).

An important step in considering alternative explanations is to seek out disconfirming evidence 4 , 63 . This involves looking for instances where participants deviate from what the majority are saying and thus bring into question the theory (or explanation) that the researcher is developing. Careful analysis of such examples can often demonstrate the salience and meaning of what appears to be the norm (see Table 2 for examples) 54 . Considering alternative explanations and paying attention to disconfirming evidence allows the researcher to refine their own theories in respect of the data.

Finally, researchers should aim for theoretical transferability and significance in their discussions of findings. One way to think about this is to imagine someone who is not interested in the empirical study. Articulating theoretical transferability and significance usually takes the form of broadening out from the specific findings to consider explicitly how the research has refined or altered prior theoretical approaches. This process also means considering under what other conditions, aside from those of the study, the researcher thinks their theoretical revision would be supported by and why. Importantly, it also includes thinking about the limitations of one’s own approach and where the theoretical implications of the study might not hold.

Box 4 An example of grounding interpretations in data (from Rao 34 )

In an article explaining how unemployed men frame their job loss as a pervasive experience, Rao writes the following: “Unemployed men in this study understood unemployment to be an expected aspect of paid work in the contemporary United States. Robert, a white unemployed communications professional, compared the economic landscape after the Great Recession with the tragic events of September 11, 2001:

Part of your post-9/11 world was knowing people that died as a result of terrorism. The same thing is true with the [Great] Recession, right? … After the Recession you know somebody who was unemployed … People that really should be working.

The pervasiveness of unemployment rendered it normal, as Robert indicates.”

Here, the link between the quote presented and the analytical point Rao is making is clear: the analytical point is grounded in a quote and an interpretation of the quote is offered 34 .

Limitations and optimizations

When deciding which research method to use, the key question is whether the method provides a good fit for the research questions posed. In other words, researchers should consider whether interviews will allow them to successfully access the social phenomena necessary to answer their question(s) and whether the interviews will do so more effectively than other methods. Table 3 summarizes the major strengths and limitations of interviews. However, the accompanying text below is organized around some key issues, where relative strengths and weaknesses are presented alongside each other, the aim being that readers should think about how these can be balanced and optimized in relation to their own research.

Breadth versus depth of insight

Achieving an overall breadth of insight, in a statistically representative sense, is not something that is possible or indeed desirable when conducting in-depth interviews. Instead, the strength of conducting interviews lies in their ability to generate various sorts of depth of insight. The experiences or views of participants that can be accessed by conducting interviews help us to understand participants’ subjective realities. The challenge, therefore, is for researchers to be clear about why depth of insight is the focus and what we should aim to glean from these types of insight.

Naturalistic or artificial interviews

Interviews make use of a form of interaction with which people are familiar 64 . By replicating a naturalistic form of interaction as a tool to gather social science data, researchers can capitalize on people’s familiarity and expectations of what happens in a conversation. This familiarity can also be a challenge, as people come to the interview with preconceived ideas about what this conversation might be for or about. People may draw on experiences of other similar conversations when taking part in a research interview (for example, job interviews, therapy sessions, confessional conversations, chats with friends). Researchers should be aware of such potential overlaps and think through their implications both in how the aims and purposes of the research interview are communicated to participants and in how interview data are interpreted.

Further, some argue that a limitation of interviews is that they are an artificial form of data collection. By taking people out of their daily lives and asking them to stand back and pass comment, we are creating a distance that makes it difficult to use such data to say something meaningful about people’s actions, experiences and views. Other approaches, such as ethnography, might be more suitable for tapping into what people actually do, as opposed to what they say they do 65 .

Dynamism and replicability

Interviews following a semi-structured format offer flexibility both to the researcher and the participant. As the conversation develops, the interlocutors can explore the topics raised in much more detail, if desired, or pass over ones that are not relevant. This flexibility allows for the unexpected and the unforeseen to be incorporated into the scope of the research.

However, this flexibility has a related challenge of replicability. Interviews cannot be reproduced because they are contingent upon the interaction between the researcher and the participant in that given moment of interaction. In some research paradigms, replicability can be a way of interrogating the robustness of research claims, by seeing whether they hold when they are repeated. This is not a useful framework to bring to in-depth interviews and instead quality criteria (such as transparency) tend to be employed as criteria of rigour.

Accessing the private and personal

Interviews have been recognized for their strength in accessing private, personal issues, which participants may feel more comfortable talking about in a one-to-one conversation. Furthermore, interviews are likely to take a more personable form with their extended questions and answers, perhaps making a participant feel more at ease when discussing sensitive topics in such a context. There is a similar, but separate, argument made about accessing what are sometimes referred to as vulnerable groups, who may be difficult to make contact with using other research methods.

There is an associated challenge of anonymity. There can be types of in-depth interview that make it particularly challenging to protect the identities of participants, such as interviewing within a small community, or multiple members of the same household. The challenge to ensure anonymity in such contexts is even more important and difficult when the topic of research is of a sensitive nature or participants are vulnerable.

Increasingly, researchers are collaborating in large-scale interview-based studies and integrating interviews into broader mixed-methods designs. At the same time, interviews can be seen as an old-fashioned (and perhaps outdated) mode of data collection. We review these debates and discussions and point to innovations in interview-based studies. These include the shift from face-to-face interviews to the use of online platforms, as well as integrating and adapting interviews towards more inclusive methodologies.

Collaborating and mixing

Qualitative researchers have long worked alone 66 . Increasingly, however, researchers are collaborating with others for reasons such as efficiency, institutional incentives (for example, funding for collaborative research) and a desire to pool expertise (for example, studying similar phenomena in different contexts 67 or via different methods). Collaboration can occur across disciplines and methods, cases and contexts and between industry/business, practitioners and researchers. In many settings and contexts, collaboration has become an imperative 68 .

Cheek notes how collaboration provides both advantages and disadvantages 68 . For example, collaboration can be advantageous, saving time and building on the divergent knowledge, skills and resources of different researchers. Scholars with different theoretical or case-based knowledge (or contacts) can work together to build research that is comparative and/or more than the sum of its parts. But such endeavours also carry with them practical and political challenges in terms of how resources might actually be pooled, shared or accounted for. When undertaking such projects, as Morse notes, it is worth thinking about the nature of the collaboration and being explicit about such a choice, its advantages and its disadvantages 66 .

A further tension, but also a motivation for collaboration, stems from integrating interviews as a method in a mixed-methods project, whether with other qualitative researchers (to combine with, for example, focus groups, document analysis or ethnography) or with quantitative researchers (to combine with, for example, surveys, social media analysis or big data analysis). Cheek and Morse both note the pitfalls of collaboration with quantitative researchers: that quality of research may be sacrificed, qualitative interpretations watered down or not taken seriously, or tensions experienced over the pace and different assumptions that come with different methods and approaches of research 66 , 68 .

At the same time, there can be real benefits of such mixed-methods collaboration, such as reaching different and more diverse audiences or testing assumptions and theories between research components in the same project (for example, testing insights from prior quantitative research via interviews, or vice versa), as long as the skillsets of collaborators are seen as equally beneficial to the project. Cheek provides a set of questions that, as a starting point, can be useful for guiding collaboration, whether mixed methods or otherwise. First, Cheek advises asking all collaborators about their assumptions and understandings concerning collaboration. Second, Cheek recommends discussing what each perspective highlights and focuses on (and conversely ignores or sidelines) 68 .

A different way to engage with the idea of collaboration and mixed methods research is by fostering greater collaboration between researchers in the Global South and Global North, thus reversing trends of researchers from the Global North extracting knowledge from the Global South 69 . Such forms of collaboration also align with interview innovations, discussed below, that seek to transform traditional interview approaches into more participatory and inclusive (as part of participatory methodologies).

Digital innovations and challenges

The ongoing COVID-19 pandemic has centred the question of technology within interview-based fieldwork. Although conducting synchronous oral interviews online — for example, via Zoom, Skype or other such platforms — has been a method used by a small constituency of researchers for many years, it became (and remains) a necessity for many researchers wanting to continue or start interview-based projects while COVID-19 prevents face-to-face data collection.

In the past, online interviews were often framed as an inferior form of data collection for not providing the kinds of (often necessary) insights and forms of immersion face-to-face interviews allow 70 , 71 . Online interviews do tend to be more decontextualized than interviews conducted face-to-face 72 . For example, it is harder to recognize, engage with and respond to non-verbal cues 71 . At the same time, they broaden participation to those who might not have been able to access or travel to sites where interviews would have been conducted otherwise, for example people with disabilities. Online interviews also offer more flexibility in terms of scheduling and time requirements. For example, they provide more flexibility around precarious employment or caring responsibilities without having to travel and be away from home. In addition, online interviews might also reduce discomfort between researchers and participants, compared with face-to-face interviews, enabling more discussion of sensitive material 71 . They can also provide participants with more control, enabling them to turn on and off the microphone and video as they choose, for example, to provide more time to reflect and disconnect if they so wish 72 .

That said, online interviews can also introduce new biases based on access to technology 72 . For example, in the Global South, there are often urban/rural and gender gaps between who has access to mobile phones and who does not, meaning that some population groups might be overlooked unless researchers sample mindfully 71 . There are also important ethical considerations when deciding between online and face-to-face interviews. Online interviews might seem to imply lower ethical risks than face-to-face interviews (for example, they lower the chances of identification of participants or researchers), but they also offer more barriers to building trust between researchers and participants 72 . Interacting only online with participants might not provide the information needed to assess risk, for example, participants’ access to a private space to speak 71 . Just because online interviews might be more likely to be conducted in private spaces does not mean that private spaces are safe, for example, for victims of domestic violence. Finally, online interviews prompt further questions about decolonizing research and engaging with participants if research is conducted from afar 72 , such as how to include participants meaningfully and challenge dominant assumptions while doing so remotely.

A further digital innovation, modulating how researchers conduct interviews and the kinds of data collected and analysed, stems from the use and integration of (new) technology, such as WhatsApp text or voice notes to conduct synchronous or asynchronous oral or written interviews 73 . Such methods can provide more privacy, comfort and control to participants and make recruitment easier, allowing participants to share what they want when they want to, using technology that already forms a part of their daily lives, especially for young people 74 , 75 . Such technology is also emerging in other qualitative methods, such as focus groups, with similar arguments around greater inclusivity versus traditional offline modes. Here, the digital challenge might be higher for researchers than for participants if they are less used to such technology 75 . And while there might be concerns about the richness, depth and quality of written messages as a form of interview data, Gibson reports that the reams of transcripts that resulted from a study using written messaging were dense with meaning to be analysed 75 .

Like with online and face-to-face interviews, it is important also to consider the ethical questions and challenges of using such technology, from gaining consent to ensuring participant safety and attending to their distress, without cues, like crying, that might be more obvious in a face-to-face setting 75 , 76 . Attention to the platform used for such interviews is also important and researchers should be attuned to the local and national context. For example, in China, many platforms are neither legal nor available 76 . There, more popular platforms — like WeChat — can be highly monitored by the government, posing potential risks to participants depending on the topic of the interview. Ultimately, researchers should consider trade-offs between online and offline interview modalities, being attentive to the social context and power dynamics involved.

The next 5–10 years

Continuing to integrate (ethically) this technology will be among the major persisting developments in interview-based research, whether to offer more flexibility to researchers or participants, or to diversify who can participate and on what terms.

Pushing the idea of inclusion even further is the potential for integrating interview-based studies within participatory methods, which are also innovating via integrating technology. There is no hard and fast line between researchers using in-depth interviews and participatory methods; many who employ participatory methods will use interviews at the beginning, middle or end phases of a research project to capture insights, perspectives and reflections from participants 77 , 78 . Participatory methods emphasize the need to resist existing power and knowledge structures. They broaden who has the right and ability to contribute to academic knowledge by including and incorporating participants not only as subjects of data collection, but as crucial voices in research design and data analysis 77 . Participatory methods also seek to facilitate local change and to produce research materials, whether for academic or non-academic audiences, including films and documentaries, in collaboration with participants.

In responding to the challenges of COVID-19, capturing the fraught situation wrought by the pandemic and the momentum to integrate technology, participatory researchers have sought to continue data collection from afar. For example, Marzi has adapted an existing project to co-produce participatory videos, via participants’ smartphones in Medellin, Colombia, alongside regular check-in conversations/meetings/interviews with participants 79 . Integrating participatory methods into interview studies offers a route by which researchers can respond to the challenge of diversifying knowledge, challenging assumptions and power hierarchies and creating more inclusive and collaborative partnerships between participants and researchers in the Global North and South.

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A pre-written interview outline for a semi-structured interview that provides both a topic structure and the ability to adapt flexibly to the content and context of the interview and the interaction between the interviewer and participant. Others may refer to the topic guide as an interview protocol.

Here we refer to the participants that take part in the study as the sample. Other researchers may refer to the participants as a participant group or dataset.

This involves dividing a population into smaller groups based on particular characteristics, for example, age or gender, and then sampling randomly within each group.

A sampling method where the guiding logic when deciding who to recruit is to achieve the most relevant participants for the research topic, in terms of being rich in information or insights.

Researchers ask participants to introduce the researcher to others who meet the study’s inclusion criteria.

Similar to stratified sampling, but participants are not necessarily randomly selected. Instead, the researcher determines how many people from each category of participants should be recruited. Recruitment can happen via snowball or purposive sampling.

A method for developing, analysing and interpreting patterns across data by coding in order to develop themes.

An approach that interrogates the explicit, implicit and taken-for-granted dimensions of language as well as the contexts in which it is articulated to unpack its purposes and effects.

A form of transcription that simplifies what has been said by removing certain verbal and non-verbal details that add no further meaning, such as ‘ums and ahs’ and false starts.

The analytic framework, theoretical approach and often hypotheses, are developed prior to examining the data and then applied to the dataset.

The analytic framework and theoretical approach is developed from analysing the data.

An approach that combines deductive and inductive components to work recursively by going back and forth between data and existing theoretical frameworks (also described as an iterative approach). This approach is increasingly recognized not only as a more realistic but also more desirable third alternative to the more traditional inductive versus deductive binary choice.

A theoretical apparatus that emphasizes the role of cultural processes and capital in (intergenerational) social reproduction.

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Handbook of Research Methods in Health Social Sciences pp 391–410 Cite as

Qualitative Interviewing

Sally Nathan 2 ,
Christy Newman 3 &
Kari Lancaster 3
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Qualitative interviewing is a foundational method in qualitative research and is widely used in health research and the social sciences. Both qualitative semi-structured and in-depth unstructured interviews use verbal communication, mostly in face-to-face interactions, to collect data about the attitudes, beliefs, and experiences of participants. Interviews are an accessible, often affordable, and effective method to understand the socially situated world of research participants. The approach is typically informed by an interpretive framework where the data collected is not viewed as evidence of the truth or reality of a situation or experience but rather a context-bound subjective insight from the participants. The researcher needs to be open to new insights and to privilege the participant’s experience in data collection. The data from qualitative interviews is not generalizable, but its exploratory nature permits the collection of rich data which can answer questions about which little is already known. This chapter introduces the reader to qualitative interviewing, the range of traditions within which interviewing is utilized as a method, and highlights the advantages and some of the challenges and misconceptions in its application. The chapter also provides practical guidance on planning and conducting interview studies. Three case examples are presented to highlight the benefits and risks in the use of interviewing with different participants, providing situated insights as well as advice about how to go about learning to interview if you are a novice.

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Nathan, S., Newman, C., Lancaster, K. (2019). Qualitative Interviewing. In: Liamputtong, P. (eds) Handbook of Research Methods in Health Social Sciences. Springer, Singapore. https://doi.org/10.1007/978-981-10-5251-4_77

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Qualitative Research 101: Interviewing

5 Common Mistakes To Avoid When Undertaking Interviews

By: David Phair (PhD) and Kerryn Warren (PhD) | March 2022

Undertaking interviews is potentially the most important step in the qualitative research process. If you don’t collect useful, useable data in your interviews, you’ll struggle through the rest of your dissertation or thesis. Having helped numerous students with their research over the years, we’ve noticed some common interviewing mistakes that first-time researchers make. In this post, we’ll discuss five costly interview-related mistakes and outline useful strategies to avoid making these.

Overview: 5 Interviewing Mistakes

Not having a clear interview strategy /plan
Not having good interview techniques /skills
Not securing a suitable location and equipment
Not having a basic risk management plan
Not keeping your “ golden thread ” front of mind

1. Not having a clear interview strategy

The first common mistake that we’ll look at is that of starting the interviewing process without having first come up with a clear interview strategy or plan of action. While it’s natural to be keen to get started engaging with your interviewees, a lack of planning can result in a mess of data and inconsistency between interviews.

There are several design choices to decide on and plan for before you start interviewing anyone. Some of the most important questions you need to ask yourself before conducting interviews include:

What are the guiding research aims and research questions of my study?
Will I use a structured, semi-structured or unstructured interview approach?
How will I record the interviews (audio or video)?
Who will be interviewed and by whom ?
What ethics and data law considerations do I need to adhere to?
How will I analyze my data?

Let’s take a quick look at some of these.

The core objective of the interviewing process is to generate useful data that will help you address your overall research aims. Therefore, your interviews need to be conducted in a way that directly links to your research aims, objectives and research questions (i.e. your “golden thread”). This means that you need to carefully consider the questions you’ll ask to ensure that they align with and feed into your golden thread. If any question doesn’t align with this, you may want to consider scrapping it.

Another important design choice is whether you’ll use an unstructured, semi-structured or structured interview approach . For semi-structured interviews, you will have a list of questions that you plan to ask and these questions will be open-ended in nature. You’ll also allow the discussion to digress from the core question set if something interesting comes up. This means that the type of information generated might differ a fair amount between interviews.

Contrasted to this, a structured approach to interviews is more rigid, where a specific set of closed questions is developed and asked for each interviewee in exactly the same order. Closed questions have a limited set of answers, that are often single-word answers. Therefore, you need to think about what you’re trying to achieve with your research project (i.e. your research aims) and decided on which approach would be best suited in your case.

It is also important to plan ahead with regards to who will be interviewed and how. You need to think about how you will approach the possible interviewees to get their cooperation, who will conduct the interviews, when to conduct the interviews and how to record the interviews. For each of these decisions, it’s also essential to make sure that all ethical considerations and data protection laws are taken into account.

Finally, you should think through how you plan to analyze the data (i.e., your qualitative analysis method) generated by the interviews. Different types of analysis rely on different types of data, so you need to ensure you’re asking the right types of questions and correctly guiding your respondents.

Simply put, you need to have a plan of action regarding the specifics of your interview approach before you start collecting data. If not, you’ll end up drifting in your approach from interview to interview, which will result in inconsistent, unusable data.

Your interview questions need to directly link to your research aims, objectives and research questions - your "golden thread”.

2. Not having good interview technique

While you’re generally not expected to become you to be an expert interviewer for a dissertation or thesis, it is important to practice good interview technique and develop basic interviewing skills .

Let’s go through some basics that will help the process along.

Firstly, before the interview , make sure you know your interview questions well and have a clear idea of what you want from the interview. Naturally, the specificity of your questions will depend on whether you’re taking a structured, semi-structured or unstructured approach, but you still need a consistent starting point . Ideally, you should develop an interview guide beforehand (more on this later) that details your core question and links these to the research aims, objectives and research questions.

Before you undertake any interviews, it’s a good idea to do a few mock interviews with friends or family members. This will help you get comfortable with the interviewer role, prepare for potentially unexpected answers and give you a good idea of how long the interview will take to conduct. In the interviewing process, you’re likely to encounter two kinds of challenging interviewees ; the two-word respondent and the respondent who meanders and babbles. Therefore, you should prepare yourself for both and come up with a plan to respond to each in a way that will allow the interview to continue productively.

To begin the formal interview , provide the person you are interviewing with an overview of your research. This will help to calm their nerves (and yours) and contextualize the interaction. Ultimately, you want the interviewee to feel comfortable and be willing to be open and honest with you, so it’s useful to start in a more casual, relaxed fashion and allow them to ask any questions they may have. From there, you can ease them into the rest of the questions.

As the interview progresses , avoid asking leading questions (i.e., questions that assume something about the interviewee or their response). Make sure that you speak clearly and slowly , using plain language and being ready to paraphrase questions if the person you are interviewing misunderstands. Be particularly careful with interviewing English second language speakers to ensure that you’re both on the same page.

Engage with the interviewee by listening to them carefully and acknowledging that you are listening to them by smiling or nodding. Show them that you’re interested in what they’re saying and thank them for their openness as appropriate. This will also encourage your interviewee to respond openly.

Need a helping hand?

3. Not securing a suitable location and quality equipment

Where you conduct your interviews and the equipment you use to record them both play an important role in how the process unfolds. Therefore, you need to think carefully about each of these variables before you start interviewing.

Poor location: A bad location can result in the quality of your interviews being compromised, interrupted, or cancelled. If you are conducting physical interviews, you’ll need a location that is quiet, safe, and welcoming . It’s very important that your location of choice is not prone to interruptions (the workplace office is generally problematic, for example) and has suitable facilities (such as water, a bathroom, and snacks).

If you are conducting online interviews , you need to consider a few other factors. Importantly, you need to make sure that both you and your respondent have access to a good, stable internet connection and electricity. Always check before the time that both of you know how to use the relevant software and it’s accessible (sometimes meeting platforms are blocked by workplace policies or firewalls). It’s also good to have alternatives in place (such as WhatsApp, Zoom, or Teams) to cater for these types of issues.

Poor equipment: Using poor-quality recording equipment or using equipment incorrectly means that you will have trouble transcribing, coding, and analyzing your interviews. This can be a major issue , as some of your interview data may go completely to waste if not recorded well. So, make sure that you use good-quality recording equipment and that you know how to use it correctly.

To avoid issues, you should always conduct test recordings before every interview to ensure that you can use the relevant equipment properly. It’s also a good idea to spot check each recording afterwards, just to make sure it was recorded as planned. If your equipment uses batteries, be sure to always carry a spare set.

Where you conduct your interviews and the equipment you use to record them play an important role in how the process unfolds.

4. Not having a basic risk management plan

Many possible issues can arise during the interview process. Not planning for these issues can mean that you are left with compromised data that might not be useful to you. Therefore, it’s important to map out some sort of risk management plan ahead of time, considering the potential risks, how you’ll minimize their probability and how you’ll manage them if they materialize.

Common potential issues related to the actual interview include cancellations (people pulling out), delays (such as getting stuck in traffic), language and accent differences (especially in the case of poor internet connections), issues with internet connections and power supply. Other issues can also occur in the interview itself. For example, the interviewee could drift off-topic, or you might encounter an interviewee who does not say much at all.

You can prepare for these potential issues by considering possible worst-case scenarios and preparing a response for each scenario. For instance, it is important to plan a backup date just in case your interviewee cannot make it to the first meeting you scheduled with them. It’s also a good idea to factor in a 30-minute gap between your interviews for the instances where someone might be late, or an interview runs overtime for other reasons. Make sure that you also plan backup questions that could be used to bring a respondent back on topic if they start rambling, or questions to encourage those who are saying too little.

In general, it’s best practice to plan to conduct more interviews than you think you need (this is called oversampling ). Doing so will allow you some room for error if there are interviews that don’t go as planned, or if some interviewees withdraw. If you need 10 interviews, it is a good idea to plan for 15. Likely, a few will cancel , delay, or not produce useful data.

You should consider all the potential risks, how you’ll reduce their probability and how you'll respond if they do indeed materialize.

5. Not keeping your golden thread front of mind

We touched on this a little earlier, but it is a key point that should be central to your entire research process. You don’t want to end up with pages and pages of data after conducting your interviews and realize that it is not useful to your research aims . Your research aims, objectives and research questions – i.e., your golden thread – should influence every design decision and should guide the interview process at all times.

A useful way to avoid this mistake is by developing an interview guide before you begin interviewing your respondents. An interview guide is a document that contains all of your questions with notes on how each of the interview questions is linked to the research question(s) of your study. You can also include your research aims and objectives here for a more comprehensive linkage.

You can easily create an interview guide by drawing up a table with one column containing your core interview questions . Then add another column with your research questions , another with expectations that you may have in light of the relevant literature and another with backup or follow-up questions . As mentioned, you can also bring in your research aims and objectives to help you connect them all together. If you’d like, you can download a copy of our free interview guide here .

Recap: Qualitative Interview Mistakes

In this post, we’ve discussed 5 common costly mistakes that are easy to make in the process of planning and conducting qualitative interviews.

To recap, these include:

If you have any questions about these interviewing mistakes, drop a comment below. Alternatively, if you’re interested in getting 1-on-1 help with your thesis or dissertation , check out our dissertation coaching service or book a free initial consultation with one of our friendly Grad Coaches.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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Harvard Library
Research Guides
Faculty of Arts & Sciences Libraries

Library Support for Qualitative Research

Interview Research
Resources for Methodology
Remote Research & Virtual Fieldwork

Resources for Research Interviewing

Nih-funded qualitative research.

Oral History
Data Management & Repositories
Campus Access

Types of Interviews

Engaging Participants

Interview Questions

Conducting Interviews
Transcription
Coding and Analysis
Managing & Finding Interview Data
UX & Market Research Interviews

Textbooks, Guidebooks, and Handbooks

The Ethnographic Interview by James P. Spradley “Spradley wrote this book for the professional and student who have never done ethnographic fieldwork (p. 231) and for the professional ethnographer who is interested in adapting the author’s procedures (p. iv). Part 1 outlines in 3 chapters Spradley’s version of ethnographic research, and it provides the background for Part 2 which consists of 12 guided steps (chapters) ranging from locating and interviewing an informant to writing an ethnography. Most of the examples come from the author’s own fieldwork among U.S. subcultures . . . Steps 6 and 8 explain lucidly how to construct a domain and a taxonomic analysis” (excerpted from book review by James D. Sexton, 1980).
Fundamentals of Qualitative Research by Johnny Saldana (Series edited by Patricia Leavy) Provides a soup-to-nuts overview of the qualitative data collection process, including interviewing, participant observation, and other methods.
InterViews by Steinar Kvale Interviewing is an essential tool in qualitative research and this introduction to interviewing outlines both the theoretical underpinnings and the practical aspects of the process. After examining the role of the interview in the research process, Steinar Kvale considers some of the key philosophical issues relating to interviewing: the interview as conversation, hermeneutics, phenomenology, concerns about ethics as well as validity, and postmodernism. Having established this framework, the author then analyzes the seven stages of the interview process - from designing a study to writing it up.
Practical Evaluation by Michael Quinn Patton Surveys different interviewing strategies, from, a) informal/conversational, to b) interview guide approach, to c) standardized and open-ended, to d) closed/quantitative. Also discusses strategies for wording questions that are open-ended, clear, sensitive, and neutral, while supporting the speaker. Provides suggestions for probing and maintaining control of the interview process, as well as suggestions for recording and transcription.
The SAGE Handbook of Interview Research by Amir B. Marvasti (Editor); James A. Holstein (Editor); Jaber F. Gubrium (Editor); Karyn D. McKinney (Editor) The new edition of this landmark volume emphasizes the dynamic, interactional, and reflexive dimensions of the research interview. Contributors highlight the myriad dimensions of complexity that are emerging as researchers increasingly frame the interview as a communicative opportunity as much as a data-gathering format. The book begins with the history and conceptual transformations of the interview, which is followed by chapters that discuss the main components of interview practice. Taken together, the contributions to The SAGE Handbook of Interview Research: The Complexity of the Craft encourage readers simultaneously to learn the frameworks and technologies of interviewing and to reflect on the epistemological foundations of the interview craft.
The SAGE Handbook of Online Research Methods by Nigel G. Fielding, Raymond M. Lee and Grant Blank (Editors) Bringing together the leading names in both qualitative and quantitative online research, this new edition is organised into nine sections: 1. Online Research Methods 2. Designing Online Research 3. Online Data Capture and Data Collection 4. The Online Survey 5. Digital Quantitative Analysis 6. Digital Text Analysis 7. Virtual Ethnography 8. Online Secondary Analysis: Resources and Methods 9. The Future of Online Social Research

ONLINE RESOURCES, COMMUNITIES, AND DATABASES

Interviews as a Method for Qualitative Research (video) This short video summarizes why interviews can serve as useful data in qualitative research.
Companion website to Bloomberg and Volpe's Completing Your Qualitative Dissertation: A Road Map from Beginning to End, 4th ed Provides helpful templates and appendices featured in the book, as well as links to other useful dissertation resources.
International Congress of Qualitative Inquiry Annual conference hosted by the International Center for Qualitative Inquiry at the University of Illinois at Urbana-Champaign, which aims to facilitate the development of qualitative research methods across a wide variety of academic disciplines, among other initiatives.
METHODSPACE An online home of the research methods community, where practicing researchers share how to make research easier.
SAGE researchmethods Researchers can explore methods concepts to help them design research projects, understand particular methods or identify a new method, conduct their research, and write up their findings. A "methods map" facilitates finding content on methods.

The decision to conduct interviews, and the type of interviewing to use, should flow from, or align with, the methodological paradigm chosen for your study, whether that paradigm is interpretivist, critical, positivist, or participative in nature (or a combination of these).

Structured:

Structured Interview. Entry in The SAGE Encyclopedia of Social Science Research Methodsby Floyd J. Fowler Jr., Editors: Michael S. Lewis-Beck; Alan E. Bryman; Tim Futing Liao (Editor) A concise article noting standards, procedures, and recommendations for developing and testing structured interviews. For an example of structured interview questions, you may view the Current Population Survey, May 2008: Public Participation in the Arts Supplement (ICPSR 29641), Apr 15, 2011 at https://doi.org/10.3886/ICPSR29641.v1 (To see the survey questions, preview the user guide, which can be found under the "Data and Documentation" tab. Then, look for page 177 (attachment 8).

Semi-Structured:

Semi-Structured Interview. Entry in The SAGE Encyclopedia of Qualitative Research Methodsby Lioness Ayres; Editor: Lisa M. Given The semi-structured interview is a qualitative data collection strategy in which the researcher asks informants a series of predetermined but open-ended questions. The researcher has more control over the topics of the interview than in unstructured interviews, but in contrast to structured interviews or questionnaires that use closed questions, there is no fixed range of responses to each question.

Unstructured:

Unstructured Interview. Entry in The SAGE Encyclopedia of Qualitative Research Methodsby Michael W. Firmin; Editor: Lisa M. Given Unstructured interviews in qualitative research involve asking relatively open-ended questions of research participants in order to discover their percepts on the topic of interest. Interviews, in general, are a foundational means of collecting data when using qualitative research methods. They are designed to draw from the interviewee constructs embedded in his or her thinking and rationale for decision making. The researcher uses an inductive method in data gathering, regardless of whether the interview method is open, structured, or semi-structured. That is, the researcher does not wish to superimpose his or her own viewpoints onto the person being interviewed. Rather, inductively, the researcher wishes to understand the participant's perceptions, helping him or her to articulate percepts such that they will be understood clearly by the journal reader.

Genres and Uses

Focus groups:.

"Focus Groups." Annual Review of Sociology 22 (1996): 129-1524.by David L. Morgan Discusses the use of focus groups and group interviews as methods for gathering qualitative data used by sociologists and other academic and applied researchers. Focus groups are recommended for giving voice to marginalized groups and revealing the group effect on opinion formation.
Qualitative Research Methods: A Data Collector's Field Guide (See Module 4: "Focus Groups")by Mack, N., et al. This field guide is based on an approach to doing team-based, collaborative qualitative research that has repeatedly proven successful in research projects sponsored by Family Health International (FHI) throughout the developing world. With its straightforward delivery of information on the main qualitative methods being used in public health research today, the guide speaks to the need for simple yet effective instruction on how to do systematic and ethically sound qualitative research. The aim of the guide is thus practical. In bypassing extensive discussion on the theoretical underpinnings of qualitative research, it distinguishes itself as a how-to guide to be used in the field.

In-Depth (typically One-on-One):

A Practical Introduction to in-Depth Interviewingby Alan Morris Are you new to qualitative research or a bit rusty and in need of some inspiration? Are you doing a research project involving in-depth interviews? Are you nervous about carrying out your interviews? This book will help you complete your qualitative research project by providing a nuts and bolts introduction to interviewing. With coverage of ethics, preparation strategies and advice for handling the unexpected in the field, this handy guide will help you get to grips with the basics of interviewing before embarking on your research. While recognising that your research question and the context of your research will drive your approach to interviewing, this book provides practical advice often skipped in traditional methods textbooks.
Qualitative Research Methods: A Data Collector's Field Guide (See Module 3: "In-Depth Interviews")by Mack, N., et al. This field guide is based on an approach to doing team-based, collaborative qualitative research that has repeatedly proven successful in research projects sponsored by Family Health International (FHI) throughout the developing world. With its straightforward delivery of information on the main qualitative methods being used in public health research today, the guide speaks to the need for simple yet effective instruction on how to do systematic and ethically sound qualitative research. The aim of the guide is thus practical. In bypassing extensive discussion on the theoretical underpinnings of qualitative research, it distinguishes itself as a how-to guide to be used in the field.

Folklore Research and Oral Histories:

In addition to the following resource, see the Oral History page of this guide for helpful resources on Oral History interviewing.

American Folklife Center at the Library of Congress. Folklife and Fieldwork: A Layman’s Introduction to Field Techniques Interviews gathered for purposes of folklore research are similar to standard social science interviews in some ways, but also have a good deal in common with oral history approaches to interviewing. The focus in a folklore research interview is on documenting and trying to understand the interviewee's way of life relative to a culture or subculture you are studying. This guide includes helpful advice and tips for conducting fieldwork in folklore, such as tips for planning, conducting, recording, and archiving interviews.

An interdisciplinary scientific program within the Institute for Quantitative Social Science which encourages and facilitates research and instruction in the theory and practice of survey research. The primary mission of PSR is to provide survey research resources to enhance the quality of teaching and research at Harvard.

Internet, Phone, Mail, and Mixed-Mode Surveysby Don A. Dillman; Jolene D. Smyth; Leah Melani Christian The classic survey design reference, updated for the digital age. The new edition is thoroughly updated and revised, and covers all aspects of survey research. It features expanded coverage of mobile phones, tablets, and the use of do-it-yourself surveys, and Dillman's unique Tailored Design Method is also thoroughly explained. This new edition is complemented by copious examples within the text and accompanying website. It includes: Strategies and tactics for determining the needs of a given survey, how to design it, and how to effectively administer it. How and when to use mail, telephone, and Internet surveys to maximum advantage. Proven techniques to increase response rates. Guidance on how to obtain high-quality feedback from mail, electronic, and other self-administered surveys. Direction on how to construct effective questionnaires, including considerations of layout. The effects of sponsorship on the response rates of surveys. Use of capabilities provided by newly mass-used media: interactivity, presentation of aural and visual stimuli. The Fourth Edition reintroduces the telephone--including coordinating land and mobile.

User Experience (UX) and Marketing:

See the "UX & Market Research Interviews" tab on this guide, above. May include Focus Groups, above.

Screening for Research Site Selection:

Research interviews are used not only to furnish research data for theoretical analysis in the social sciences, but also to plan other kinds of studies. For example, interviews may allow researchers to screen appropriate research sites to conduct empirical studies (such as randomized controlled trials) in a variety of fields, from medicine to law. In contrast to interviews conducted in the course of social research, such interviews do not typically serve as the data for final analysis and publication.

ENGAGING PARTICIPANTS

Research ethics .

Human Subjects (IRB) The Committee on the Use of Human Subjects (CUHS) serves as the Institutional Review Board for the University area which includes the Cambridge and Allston campuses at Harvard. Find your IRB contact person , or learn about required ethics training. You may also find the IRB Lifecycle Guide helpful. This is the preferred IRB portal for Harvard graduate students and other researchers. IRB forms can be downloaded via the ESTR Library (click on the "Templates and Forms" tab, then navigate to pages 2 and 3 to find the documents labelled with “HUA” for the Harvard University Area IRB. Nota bene: You may use these forms only if you submit your study to the Harvard University IRB). The IRB office can be reached through email at [email protected] or by telephone at (617) 496-2847.
Undergraduate Research Training Program (URTP) Portal The URTP at Harvard University is a comprehensive platform to create better prepared undergraduate researchers. The URTP is comprised of research ethics training sessions, a student-focused curriculum, and an online decision form that will assist students in determining whether their project requires IRB review. Students should examine the URTP's guide for student researchers: Introduction to Human Subjects Research Protection.
Ethics reports From the Association of Internet Researchers (AoIR)
Respect, Beneficence, and Justice: QDR General Guidance for Human Participants If you are hoping to share your qualitative interview data in a repository after it has been collected, you will need to plan accordingly via informed consent, careful de-identification procedures, and data access controls. Consider consulting with the Qualitative Research Support Group at Harvard Library and consulting with Harvard's Dataverse contacts to help you think through all of the contingencies and processes.
"Conducting a Qualitative Child Interview: Methodological Considerations." Journal of Advanced Nursing 42/5 (2003): 434-441 by Kortesluoma, R., et al. The purpose of this article is to illustrate the theoretical premises of child interviewing, as well as to describe some practical methodological solutions used during interviews. Factors that influence data gathered from children and strategies for taking these factors into consideration during the interview are also described.
"Crossing Cultural Barriers in Research Interviewing." Qualitative Social Work 63/3 (2007): 353-372 by Sands, R., et al. This article critically examines a qualitative research interview in which cultural barriers between a white non-Muslim female interviewer and an African American Muslim interviewee, both from the USA, became evident and were overcome within the same interview.
Decolonizing Methodologies: Research and Indigenous Peoples by Linda Tuhiwai Smith This essential volume explores intersections of imperialism and research - specifically, the ways in which imperialism is embedded in disciplines of knowledge and tradition as 'regimes of truth.' Concepts such as 'discovery' and 'claiming' are discussed and an argument presented that the decolonization of research methods will help to reclaim control over indigenous ways of knowing and being. The text includes case-studies and examples, and sections on new indigenous literature and the role of research in indigenous struggles for social justice.

This resource, sponsored by University of Oregon Libraries, exemplifies the use of interviewing methodologies in research that foregrounds traditional knowledge. The methodology page summarizes the approach.

Ethics: The Need to Tread Carefully. Chapter in A Practical Introduction to in-Depth Interviewing by Alan Morris Pay special attention to the sections in chapter 2 on "How to prevent and respond to ethical issues arising in the course of the interview," "Ethics in the writing up of your interviews," and "The Ethics of Care."
Handbook on Ethical Issues in Anthropology by Joan Cassell (Editor); Sue-Ellen Jacobs (Editor) This publication of the American Anthropological Association presents and discusses issues and sources on ethics in anthropology, as well as realistic case studies of ethical dilemmas. It is meant to help social science faculty introduce discussions of ethics in their courses. Some of the topics are relevant to interviews, or at least to studies of which interviews are a part. See chapters 3 and 4 for cases, with solutions and commentary, respectively.
Research Ethics from the Chanie Wenjack School for Indigenous Studies, Trent University (Open Access) An overview of Indigenous research ethics and protocols from the across the globe.
Resources for Equity in Research Consult these resources for guidance on creating and incorporating equitable materials into public health research studies that entail community engagement.

The SAGE Handbook of Qualitative Research Ethics by Ron Iphofen (Editor); Martin Tolich (Editor) This handbook is a much-needed and in-depth review of the distinctive set of ethical considerations which accompanies qualitative research. This is particularly crucial given the emergent, dynamic and interactional nature of most qualitative research, which too often allows little time for reflection on the important ethical responsibilities and obligations. Contributions from leading international researchers have been carefully organized into six key thematic sections: Part One: Thick Descriptions Of Qualitative Research Ethics; Part Two: Qualitative Research Ethics By Technique; Part Three: Ethics As Politics; Part Four: Qualitative Research Ethics With Vulnerable Groups; Part Five: Relational Research Ethics; Part Six: Researching Digitally. This Handbook is a one-stop resource on qualitative research ethics across the social sciences that draws on the lessons learned and the successful methods for surmounting problems - the tried and true, and the new.

RESEARCH COMPLIANCE AND PRIVACY LAWS

Research Compliance Program for FAS/SEAS at Harvard : The Faculty of Arts and Sciences (FAS), including the School of Engineering and Applied Sciences (SEAS), and the Office of the Vice Provost for Research (OVPR) have established a shared Research Compliance Program (RCP). An area of common concern for interview studies is international projects and collaboration . RCP is a resource to provide guidance on which international activities may be impacted by US sanctions on countries, individuals, or entities and whether licenses or other disclosure are required to ship or otherwise share items, technology, or data with foreign collaborators.

Harvard Global Support Services (GSS) is for students, faculty, staff, and researchers who are studying, researching, or working abroad. Their services span safety and security, health, culture, outbound immigration, employment, financial and legal matters, and research center operations. These include travel briefings and registration, emergency response, guidance on international projects, and managing in-country operations.

Generative AI: Harvard-affiliated researchers should not enter data classified as confidential ( Level 2 and above ), including non-public research data, into publicly-available generative AI tools, in accordance with the University’s Information Security Policy. Information shared with generative AI tools using default settings is not private and could expose proprietary or sensitive information to unauthorized parties.

Privacy Laws: Be mindful of any potential privacy laws that may apply wherever you conduct your interviews. The General Data Protection Regulation is a high-profile example (see below):

General Data Protection Regulation (GDPR) This Regulation lays down rules relating to the protection of natural persons with regard to the processing of personal data and rules relating to the free movement of personal data. It protects fundamental rights and freedoms of natural persons and in particular their right to the protection of personal data. The free movement of personal data within the Union shall be neither restricted nor prohibited for reasons connected with the protection of natural persons with regard to the processing of personal data. For a nice summary of what the GDPR requires, check out the GDPR "crash course" here .

SEEKING CONSENT

If you would like to see examples of consent forms, ask your local IRB, or take a look at these resources:

Model consent forms for oral history, suggested by the Centre for Oral History and Digital Storytelling at Concordia University
For NIH-funded research, see this resource for developing informed consent language in research studies where data and/or biospecimens will be stored and shared for future use.

POPULATION SAMPLING

If you wish to assemble resources to aid in sampling, such as the USPS Delivery Sequence File, telephone books, or directories of organizations and listservs, please contact our data librarian or write to [email protected] .

Research Randomizer A free web-based service that permits instant random sampling and random assignment. It also contains an interactive tutorial perfect for students taking courses in research methods.
Practical Tools for Designing and Weighting Survey Samples by Richard Valliant; Jill A. Dever; Frauke Kreuter Survey sampling is fundamentally an applied field. The goal in this book is to put an array of tools at the fingertips of practitioners by explaining approaches long used by survey statisticians, illustrating how existing software can be used to solve survey problems, and developing some specialized software where needed. This book serves at least three audiences: (1) Students seeking a more in-depth understanding of applied sampling either through a second semester-long course or by way of a supplementary reference; (2) Survey statisticians searching for practical guidance on how to apply concepts learned in theoretical or applied sampling courses; and (3) Social scientists and other survey practitioners who desire insight into the statistical thinking and steps taken to design, select, and weight random survey samples. Several survey data sets are used to illustrate how to design samples, to make estimates from complex surveys for use in optimizing the sample allocation, and to calculate weights. Realistic survey projects are used to demonstrate the challenges and provide a context for the solutions. The book covers several topics that either are not included or are dealt with in a limited way in other texts. These areas include: sample size computations for multistage designs; power calculations related to surveys; mathematical programming for sample allocation in a multi-criteria optimization setting; nuts and bolts of area probability sampling; multiphase designs; quality control of survey operations; and statistical software for survey sampling and estimation. An associated R package, PracTools, contains a number of specialized functions for sample size and other calculations. The data sets used in the book are also available in PracTools, so that the reader may replicate the examples or perform further analyses.
Sampling: Design and Analysis by Sharon L. Lohr Provides a modern introduction to the field of sampling. With a multitude of applications from a variety of disciplines, the book concentrates on the statistical aspects of taking and analyzing a sample. Overall, the book gives guidance on how to tell when a sample is valid or not, and how to design and analyze many different forms of sample surveys.
Sampling Techniques by William G. Cochran Clearly demonstrates a wide range of sampling methods now in use by governments, in business, market and operations research, social science, medicine, public health, agriculture, and accounting. Gives proofs of all the theoretical results used in modern sampling practice. New topics in this edition include the approximate methods developed for the problem of attaching standard errors or confidence limits to nonlinear estimates made from the results of surveys with complex plans.
"Understanding the Process of Qualitative Data Collection" in Chapter 13 (pp. 103–1162) of 30 Essential Skills for the Qualitative Researcher by John W. Creswell Provides practical "how-to" information for beginning researchers in the social, behavioral, and health sciences with many applied examples from research design, qualitative inquiry, and mixed methods.The skills presented in this book are crucial for a new qualitative researcher starting a qualitative project.
Survey Methodology by Robert M. Groves; Floyd J. Fowler; Mick P. Couper; James M. Lepkowski; Eleanor Singer; Roger Tourangeau; Floyd J. Fowler coverage includes sampling frame evaluation, sample design, development of questionnaires, evaluation of questions, alternative modes of data collection, interviewing, nonresponse, post-collection processing of survey data, and practices for maintaining scientific integrity.

The way a qualitative researcher constructs and approaches interview questions should flow from, or align with, the methodological paradigm chosen for the study, whether that paradigm is interpretivist, critical, positivist, or participative in nature (or a combination of these).

Constructing Your Questions

Helpful texts:.

"Developing Questions" in Chapter 4 (pp. 98–108) of Becoming Qualitative Researchers by Corrine Glesne Ideal for introducing the novice researcher to the theory and practice of qualitative research, this text opens students to the diverse possibilities within this inquiry approach, while helping them understand how to design and implement specific research methods.
"Learning to Interview in the Social Sciences" Qualitative Inquiry, 9(4) 2003, 643–668 by Roulston, K., deMarrais, K., & Lewis, J. B. See especially the section on "Phrasing and Negotiating Questions" on pages 653-655 and common problems with framing questions noted on pages 659 - 660.
Qualitative Research Interviewing: Biographic Narrative and Semi-Structured Methods (See sections on “Lightly and Heavily Structured Depth Interviewing: Theory-Questions and Interviewer-Questions” and “Preparing for any Interviewing Sequence") by Tom Wengraf Unique in its conceptual coherence and the level of practical detail, this book provides a comprehensive resource for those concerned with the practice of semi-structured interviewing, the most commonly used interview approach in social research, and in particular for in-depth, biographic narrative interviewing. It covers the full range of practices from the identification of topics through to strategies for writing up research findings in diverse ways.
"Scripting a Qualitative Purpose Statement and Research Questions" in Chapter 12 (pp. 93–102) of 30 Essential Skills for the Qualitative Researcher by John W. Creswell Provides practical "how-to" information for beginning researchers in the social, behavioral, and health sciences with many applied examples from research design, qualitative inquiry, and mixed methods.The skills presented in this book are crucial for a new qualitative researcher starting a qualitative project.
Some Strategies for Developing Interview Guides for Qualitative Interviews by Sociology Department, Harvard University Includes general advice for conducting qualitative interviews, pros and cons of recording and transcription, guidelines for success, and tips for developing and phrasing effective interview questions.
Tip Sheet on Question Wording by Harvard University Program on Survey Research

Let Theory Guide You:

The quality of your questions depends on how you situate them within a wider body of knowledge. Consider the following advice:

A good literature review has many obvious virtues. It enables the investigator to define problems and assess data. It provides the concepts on which percepts depend. But the literature review has a special importance for the qualitative researcher. This consists of its ability to sharpen his or her capacity for surprise (Lazarsfeld, 1972b). The investigator who is well versed in the literature now has a set of expectations the data can defy. Counterexpectational data are conspicuous, readable, and highly provocative data. They signal the existence of unfulfilled theoretical assumptions, and these are, as Kuhn (1962) has noted, the very origins of intellectual innovation. A thorough review of the literature is, to this extent, a way to manufacture distance. It is a way to let the data of one's research project take issue with the theory of one's field.

McCracken, G. (1988), The Long Interview, Sage: Newbury Park, CA, p. 31

When drafting your interview questions, remember that everything follows from your central research question. Also, on the way to writing your "operationalized" interview questions, it's helpful to draft broader, intermediate questions, couched in theory. Nota bene: While it is important to know the literature well before conducting your interview(s), be careful not to present yourself to your research participant(s) as "the expert," which would be presumptuous and could be intimidating. Rather, the purpose of your knowledge is to make you a better, keener listener.

If you'd like to supplement what you learned about relevant theories through your coursework and literature review, try these sources:

Annual Reviews Review articles sum up the latest research in many fields, including social sciences, biomedicine, life sciences, and physical sciences. These are timely collections of critical reviews written by leading scientists.
HOLLIS - search for resources on theories in your field Modify this example search by entering the name of your field in place of "your discipline," then hit search.
Oxford Bibliographies Written and reviewed by academic experts, every article in this database is an authoritative guide to the current scholarship in a variety of fields, containing original commentary and annotations.
ProQuest Dissertations & Theses (PQDT) Indexes dissertations and masters' theses from most North American graduate schools as well as some European universities. Provides full text for most indexed dissertations from 1990-present.
Very Short Introductions Launched by Oxford University Press in 1995, Very Short Introductions offer concise introductions to a diverse range of subjects from Climate to Consciousness, Game Theory to Ancient Warfare, Privacy to Islamic History, Economics to Literary Theory.

CONDUCTING INTERVIEWS

Equipment and software: .

Lamont Library loans microphones and podcast starter kits, which will allow you to capture audio (and you may record with software, such as Garage Band).
Cabot Library loans digital recording devices, as well as USB microphones.

If you prefer to use your own device, you may purchase a small handheld audio recorder, or use your cell phone.

Audio Capture Basics (PDF) - Helpful instructions, courtesy of the Lamont Library Multimedia Lab.
Getting Started with Podcasting/Audio: Guidelines from Harvard Library's Virtual Media Lab for preparing your interviewee for a web-based recording (e.g., podcast, interview)
Camtasia Screen Recorder and Video Editor
Zoom: Video Conferencing, Web Conferencing
Visit the Multimedia Production Resources guide! Consult it to find and learn how to use audiovisual production tools, including: cameras, microphones, studio spaces, and other equipment at Cabot Science Library and Lamont Library.
Try the virtual office hours offered by the Lamont Multimedia Lab!

TIPS FOR CONDUCTING INTERVIEWS

Quick handout: .

Research Interviewing Tips (Courtesy of Dr. Suzanne Spreadbury)

Remote Interviews:

For Online or Distant Interviews, See "Remote Research & Virtual Fieldwork" on this guide .
Deborah Lupton's Bibliography: Doing Fieldwork in a Pandemic

Seeking Consent:

Books and articles: .

"App-Based Textual Interviews: Interacting With Younger Generations in a Digitalized Social Reallity."International Journal of Social Research Methodology (12 June 2022). Discusses the use of texting platforms as a means to reach young people. Recommends useful question formulations for this medium.
"Learning to Interview in the Social Sciences." Qualitative Inquiry, 9(4) 2003, 643–668 by Roulston, K., deMarrais, K., & Lewis, J. B. See especially the section on "Phrasing and Negotiating Questions" on pages 653-655 and common problems with framing questions noted on pages 659-660.
"Slowing Down and Digging Deep: Teaching Students to Examine Interview Interaction in Depth." LEARNing Landscapes, Spring 2021 14(1) 153-169 by Herron, Brigette A. and Kathryn Roulston. Suggests analysis of videorecorded interviews as a precursor to formulating one's own questions. Includes helpful types of probes.
Using Interviews in a Research Project by Nigel Joseph Mathers; Nicholas J Fox; Amanda Hunn; Trent Focus Group. A work pack to guide researchers in developing interviews in the healthcare field. Describes interview structures, compares face-to-face and telephone interviews. Outlines the ways in which different types of interview data can be analysed.
“Working through Challenges in Doing Interview Research.” International Journal of Qualitative Methods, (December 2011), 348–66 by Roulston, Kathryn. The article explores (1) how problematic interactions identified in the analysis of focus group data can lead to modifications in research design, (2) an approach to dealing with reported data in representations of findings, and (3) how data analysis can inform question formulation in successive rounds of data generation. Findings from these types of examinations of interview data generation and analysis are valuable for informing both interview practice as well as research design.

Videos:

The way a qualitative researcher transcribes interviews should flow from, or align with, the methodological paradigm chosen for the study, whether that paradigm is interpretivist, critical, positivist, or participative in nature (or a combination of these).

TRANSCRIPTION

Before embarking on a transcription project, it's worthwhile to invest in the time and effort necessary to capture good audio, which will make the transcription process much easier. If you haven't already done so, check out the audio capture guidelines from Harvard Library's Virtual Media Lab , or contact a media staff member for customized recommendations. First and foremost, be mindful of common pitfalls by watching this short video that identifies the most common errors to avoid!

SOFTWARE:

Adobe Premiere Pro Speech-To-Text automatically generates transcripts and adds captions to your videos. Harvard affiliates can download Adobe Premiere in the Creative Cloud Suite.
GoTranscript provides cost-effective human-generated transcriptions.
pyTranscriber is an app for generating automatic transcription and/or subtitles for audio and video files. It uses the Google Cloud Speech-to-Text service, has a friendly graphical user interface, and is purported to work nicely with Chinese.
Otter provides a new way to capture, store, search and share voice conversations, lectures, presentations, meetings, and interviews. The startup is based in Silicon Valley with a team of experienced Ph.Ds and engineers from Google, Facebook, Yahoo and Nuance (à la Dragon). Free accounts available. This is the software that Zoom uses to generate automated transcripts, so if you have access to a Zoom subscription, you have access to Otter transcriptions with it (applicable in several languages ). As with any automated approach, be prepared to correct any errors after the fact, by hand.
Panopto is available to Harvard affiliates and generates ASR (automated speech recognition) captions . You may upload compatible audio files into it. As with any automatically generated transcription, you will need to make manual revisions. ASR captioning is available in several languages . Panopto maintains robust security practices, including strong authentication measures and end-to-end encryption, ensuring your content remains private and protected.
REV.Com allows you to record and transcribe any calls on the iPhone, both outgoing and incoming. It may be useful for recording phone interviews. Rev lets you choose whether you want an AI- or human-generated transcription, with a fast turnaround. Rev has Service Organization Controls Type II (SOC2) certification (a SOC2 cert looks at and verifies an organization’s processing integrity, privacy practices, and security safeguards).
Scribie Audio/Video Transcription provides automated or manual transcriptions for a small fee. As with any transcription service, some revisions will be necessary after the fact, particularly for its automated transcripts.
Sonix automatically transcribes, translates, and helps to organize audio and video files in over 40 languages. It's fast and affordable, with good accuracy. The free trial includes 30 minutes of free transcription.
TranscriptionWing uses a human touch process to clean up machine-generated transcripts so that the content will far more accurately reflect your audio recording.
Whisper is a tool from OpenAI that facilitates transcription of sensitive audiovisual recordings (e.g., of research interviews) on your own device. Installation and use depends on your operating system and which version you install. Important Note: The Whisper API, where audio is sent to OpenAI to be processed by them and then sent back (usually through a programming language like Python) is NOT appropriate for sensitive data. The model should be downloaded with tools such as those described in this FAQ , so that audio is kept to your local machine. For assistance, contact James Capobianco .

EQUIPMENT:

Transcription pedals are in circulation and available to borrow from the Circulation desk at Lamont, or use at Lamont Library's Media Lab on level B. For hand-transcribing your interviews, they work in conjunction with software such as Express Scribe , which is loaded on Media Lab computers, or you may download for free on your own machine (Mac or PC versions; scroll down the downloads page for the latter). The pedals are plug-and-play USB, allow a wide range of playback speeds, and have 3 programmable buttons, which are typically set to rewind/play/fast-forward. Instructions are included in the bag that covers installation and set-up of the software, and basic use of the pedals.

NEED HELP?

Try the virtual office hours offered by the Lamont Multimedia Lab!
If you're creating podcasts, login to Canvas and check out the Podcasting/Audio guide .

Helpful Texts:

"Transcription as a Crucial Step of Data Analysis" in Chapter 5 of The SAGE Handbook of Qualitative Data Analysisby Uwe Flick (Editor) Covers basic terminology for transcription, shares caveats for transcribers, and identifies components of vocal behavior. Provides notation systems for transcription, suggestions for transcribing turn-taking, and discusses new technologies and perspectives. Includes a bibliography for further reading.
"Transcribing the Oral Interview: Part Art, Part Science " on p. 10 of the Centre for Community Knowledge (CCK) newsletter: TIMESTAMPby Mishika Chauhan and Saransh Srivastav

QUALITATIVE DATA ANALYSIS

Software .

Free download available for Harvard Faculty of Arts and Sciences (FAS) affiliates
Desktop access at Lamont Library Media Lab, 3rd floor
Desktop access at Harvard Kennedy School Library (with HKS ID)
Remote desktop access for Harvard affiliates from IQSS Computer Labs . Email them at [email protected] and ask for a new lab account and remote desktop access to NVivo.
Virtual Desktop Infrastructure (VDI) access available to Harvard T.H. Chan School of Public Health affiliates

CODING AND THEMEING YOUR DATA

Data analysis methods should flow from, or align with, the methodological paradigm chosen for your study, whether that paradigm is interpretivist, critical, positivist, or participative in nature (or a combination of these). Some established methods include Content Analysis, Critical Analysis, Discourse Analysis, Gestalt Analysis, Grounded Theory Analysis, Interpretive Analysis, Narrative Analysis, Normative Analysis, Phenomenological Analysis, Rhetorical Analysis, and Semiotic Analysis, among others. The following resources should help you navigate your methodological options and put into practice methods for coding, themeing, interpreting, and presenting your data.

Users can browse content by topic, discipline, or format type (reference works, book chapters, definitions, etc.). SRM offers several research tools as well: a methods map, user-created reading lists, a project planner, and advice on choosing statistical tests.
Abductive Coding: Theory Building and Qualitative (Re)Analysis by Vila-Henninger, et al. The authors recommend an abductive approach to guide qualitative researchers who are oriented towards theory-building. They outline a set of tactics for abductive analysis, including the generation of an abductive codebook, abductive data reduction through code equations, and in-depth abductive qualitative analysis.
Analyzing and Interpreting Qualitative Research: After the Interview by Charles F. Vanover, Paul A. Mihas, and Johnny Saldana (Editors) Providing insight into the wide range of approaches available to the qualitative researcher and covering all steps in the research process, the authors utilize a consistent chapter structure that provides novice and seasoned researchers with pragmatic, "how-to" strategies. Each chapter author introduces the method, uses one of their own research projects as a case study of the method described, shows how the specific analytic method can be used in other types of studies, and concludes with three questions/activities to prompt class discussion or personal study.
"Analyzing Qualitative Data." Theory Into Practice 39, no. 3 (2000): 146-54 by Margaret D. LeCompte This article walks readers though rules for unbiased data analysis and provides guidance for getting organized, finding items, creating stable sets of items, creating patterns, assembling structures, and conducting data validity checks.
"Coding is Not a Dirty Word" in Chapter 1 (pp. 1–30) of Enhancing Qualitative and Mixed Methods Research with Technology by Shalin Hai-Jew (Editor) Current discourses in qualitative research, especially those situated in postmodernism, represent coding and the technology that assists with coding as reductive, lacking complexity, and detached from theory. In this chapter, the author presents a counter-narrative to this dominant discourse in qualitative research. The author argues that coding is not necessarily devoid of theory, nor does the use of software for data management and analysis automatically render scholarship theoretically lightweight or barren. A lack of deep analytical insight is a consequence not of software but of epistemology. Using examples informed by interpretive and critical approaches, the author demonstrates how NVivo can provide an effective tool for data management and analysis. The author also highlights ideas for critical and deconstructive approaches in qualitative inquiry while using NVivo. By troubling the positivist discourse of coding, the author seeks to create dialogic spaces that integrate theory with technology-driven data management and analysis, while maintaining the depth and rigor of qualitative research.
The Coding Manual for Qualitative Researchers by Johnny Saldana An in-depth guide to the multiple approaches available for coding qualitative data. Clear, practical and authoritative, the book profiles 32 coding methods that can be applied to a range of research genres from grounded theory to phenomenology to narrative inquiry. For each approach, Saldaña discusses the methods, origins, a description of the method, practical applications, and a clearly illustrated example with analytic follow-up. Essential reading across the social sciences.
Flexible Coding of In-depth Interviews: A Twenty-first-century Approach by Nicole M. Deterding and Mary C. Waters The authors suggest steps in data organization and analysis to better utilize qualitative data analysis technologies and support rigorous, transparent, and flexible analysis of in-depth interview data.
From the Editors: What Grounded Theory is Not by Roy Suddaby Walks readers through common misconceptions that hinder grounded theory studies, reinforcing the two key concepts of the grounded theory approach: (1) constant comparison of data gathered throughout the data collection process and (2) the determination of which kinds of data to sample in succession based on emergent themes (i.e., "theoretical sampling").
“Good enough” methods for life-story analysis, by Wendy Luttrell. In Quinn N. (Ed.), Finding culture in talk (pp. 243–268). Demonstrates for researchers of culture and consciousness who use narrative how to concretely document reflexive processes in terms of where, how and why particular decisions are made at particular stages of the research process.
Presentation slides on coding and themeing your data, derived from Saldana, Spradley, and LeCompte Click to request access.
Qualitative Data Analysis by Matthew B. Miles; A. Michael Huberman A practical sourcebook for researchers who make use of qualitative data, presenting the current state of the craft in the design, testing, and use of qualitative analysis methods. Strong emphasis is placed on data displays matrices and networks that go beyond ordinary narrative text. Each method of data display and analysis is described and illustrated.
"A Survey of Qualitative Data Analytic Methods" in Chapter 4 (pp. 89–138) of Fundamentals of Qualitative Research by Johnny Saldana Provides an in-depth introduction to coding as a heuristic, particularly focusing on process coding, in vivo coding, descriptive coding, values coding, dramaturgical coding, and versus coding. Includes advice on writing analytic memos, developing categories, and themeing data.
"Thematic Networks: An Analytic Tool for Qualitative Research." Qualitative Research : QR, 1(3), 385–405 by Jennifer Attride-Stirling Details a technique for conducting thematic analysis of qualitative material, presenting a step-by-step guide of the analytic process, with the aid of an empirical example. The analytic method presented employs established, well-known techniques; the article proposes that thematic analyses can be usefully aided by and presented as thematic networks.
Using Thematic Analysis in Psychology by Virginia Braun and Victoria Clark Walks readers through the process of reflexive thematic analysis, step by step. The method may be adapted in fields outside of psychology as relevant. Pair this with One Size Fits All? What Counts as Quality Practice in Reflexive Thematic Analysis? by Virginia Braun and Victoria Clark

TESTING OR GENERATING THEORIES

The quality of your data analysis depends on how you situate what you learn within a wider body of knowledge. Consider the following advice:

Once you have coalesced around a theory, realize that a theory should reveal rather than color your discoveries. Allow your data to guide you to what's most suitable. Grounded theory researchers may develop their own theory where current theories fail to provide insight. This guide on Theoretical Models from Alfaisal University Library provides a helpful overview on using theory.

MANAGING & FINDING INTERVIEW DATA

Managing your elicited interview data, general guidance: .

Research Data Management @ Harvard A reference guide with information and resources to help you manage your research data. See also: Harvard Research Data Security Policy , on the Harvard University Research Data Management website.
Data Management For Researchers: Organize, Maintain and Share Your Data for Research Success by Kristin Briney. A comprehensive guide for scientific researchers providing everything they need to know about data management and how to organize, document, use and reuse their data.
Open Science Framework (OSF) An open-source project management tool that makes it easy to collaborate within and beyond Harvard throughout a project's lifecycle. With OSF you can manage, store, and share documents, datasets, and other information with your research team. You can also publish your work to share it with a wider audience. Although data can be stored privately, because this platform is hosted on the Internet and designed with open access in mind, it is not a good choice for highly sensitive data.
Free cloud storage solutions for Harvard affiliates to consider include: Google Drive , DropBox , or OneDrive ( up to DSL3 )

Data Confidentiality and Secure Handling:

Data Security Levels at Harvard - Research Data Examples This resource provided by Harvard Data Security helps you determine what level of access is appropriate for your data. Determine whether it should be made available for public use, limited to the Harvard community, or be protected as either "confidential and sensitive," "high risk," or "extremely sensitive." See also: Harvard Data Classification Table
Harvard's Best Practices for Protecting Privacy and Harvard Information Security Collaboration Tools Matrix Follow the nuts-and-bolts advice for privacy best practices at Harvard. The latter resource reveals the level of security that can be relied upon for a large number of technological tools and platforms used at Harvard to conduct business, such as email, Slack, Accellion Kiteworks, OneDrive/SharePoint, etc.
“Protecting Participant Privacy While Maintaining Content and Context: Challenges in Qualitative Data De‐identification and Sharing.” Proceedings of the ASIST Annual Meeting 57 (1) (2020): e415-420 by Myers, Long, and Polasek Presents an informed and tested protocol, based on the De-Identification guidelines published by the Qualitative Data Repository (QDR) at Syracuse University. Qualitative researchers may consult it to guide their data de-identification efforts.
QDS Qualitative Data Sharing Toolkit The Qualitative Data Sharing (QDS) project and its toolkit was funded by the NIH National Human Genome Research Institute (R01HG009351). It provides tools and resources to help researchers, especially those in the health sciences, share qualitative research data while protecting privacy and confidentiality. It offers guidance on preparing data for sharing through de-identification and access control. These health sciences research datasets in ICPSR's Qualitative Data Sharing (QDS) Project Series were de-identified using the QuaDS Software and the project’s QDS guidelines.
Table of De-Identification Techniques
Generative AI Harvard-affiliated researchers should not enter data classified as confidential ( Level 2 and above ), including non-public research data, into publicly-available generative AI tools, in accordance with the University’s Information Security Policy. Information shared with generative AI tools using default settings is not private and could expose proprietary or sensitive information to unauthorized parties.
Harvard Information Security Quick Reference Guide Storage guidelines, based on the data's security classification level (according to its IRB classification) is displayed on page 2, under "handling."
Email Encryption Harvard Microsoft 365 users can now send encrypted messages and files directly from the Outlook web or desktop apps. Encrypting an email adds an extra layer of security to the message and its attachments (up to 150MB), and means only the intended recipient (and their inbox delegates with full access) can view it. Message encryption in Outlook is approved for sending high risk ( level 4 ) data and below.

Sharing Qualitative Data:

Repositories for Qualitative Data If you have cleared this intention with your IRB, secured consent from participants, and properly de-identified your data, consider sharing your interviews in one of the data repositories included in the link above. Depending on the nature of your research and the level of risk it may present to participants, sharing your interview data may not be appropriate. If there is any chance that sharing such data will be desirable, you will be much better off if you build this expectation into your plans from the beginning.
Guide for Sharing Qualitative Data at ICPSR The Inter-university Consortium for Political and Social Research (ICPSR) has created this resource for investigators planning to share qualitative data at ICPSR. This guide provides an overview of elements and considerations for archiving qualitative data, identifies steps for investigators to follow during the research life cycle to ensure that others can share and reuse qualitative data, and provides information about exemplars of qualitative data

International Projects:

Research Compliance Program for FAS/SEAS at Harvard The Faculty of Arts and Sciences (FAS), including the School of Engineering and Applied Sciences (SEAS), and the Office of the Vice Provost for Research (OVPR) have established a shared Research Compliance Program (RCP). An area of common concern for interview studies is international projects and collaboration . RCP is a resource to provide guidance on which international activities may be impacted by US sanctions on countries, individuals, or entities and whether licenses or other disclosure are required to ship or otherwise share items, technology, or data with foreign collaborators.

Finding Extant Interview Data

Finding journalistic interviews: .

Academic Search Premier This all-purpose database is great for finding articles from magazines and newspapers. In the Advanced Search, it allows you to specify "Document Type": Interview.
Guide to Newspapers and Newspaper Indexes Use this guide created to Harvard Librarians to identify newspapers collections you'd like to search. To locate interviews, try adding the term "interview" to your search, or explore a database's search interface for options to limit your search to interviews. Nexis Uni and Factiva are the two main databases for current news.
Listen Notes Search for podcast episodes at this podcast aggregator, and look for podcasts that include interviews. Make sure to vet the podcaster for accuracy and quality! (Listen Notes does not do much vetting.)
NPR and ProPublica are two sites that offer high-quality long-form reporting, including journalistic interviews, for free.

Finding Oral History and Social Research Interviews:

To find oral histories, see the Oral History page of this guide for helpful resources on Oral History interviewing.
Repositories for Qualitative Data It has not been a customary practice among qualitative researchers in the social sciences to share raw interview data, but some have made this data available in repositories, such as the ones listed on the page linked above. You may find published data from structured interview surveys (e.g., questionnaire-based computer-assisted telephone interview data), as well as some semi-structured and unstructured interviews.
If you are merely interested in studies interpreting data collected using interviews, rather than finding raw interview data, try databases like PsycInfo , Sociological Abstracts , or Anthropology Plus , among others.

Finding Interviews in Archival Collections at Harvard Library:

In addition to the databases and search strategies mentioned under the "Finding Oral History and Social Research Interviews" category above, you may search for interviews and oral histories (whether in textual or audiovisual formats) held in archival collections at Harvard Library.

HOLLIS searches all documented collections at Harvard, whereas HOLLIS for Archival Discovery searches only those with finding aids. Although HOLLIS for Archival Discovery covers less material, you may find it easier to parse your search results, especially when you wish to view results at the item level (within collections). Try these approaches:

Search in HOLLIS :

To retrieve items available online, do an Advanced Search for interview* OR "oral histor*" (in Subject), with Resource Type "Archives/Manuscripts," then refine your search by selecting "Online" under "Show Only" on the right of your initial result list. Revise the search above by adding your topic in the Keywords or Subject field (for example: African Americans ) and resubmitting the search.
To enlarge your results set, you may also leave out the "Online" refinement; if you'd like to limit your search to a specific repository, try the technique of searching for Code: Library + Collection on the "Advanced Search" page .

Search in HOLLIS for Archival Discovery :

To retrieve items available online, search for interview* OR "oral histor*" limited to digital materials . Revise the search above by adding your topic (for example: artist* ) in the second search box (if you don't see the box, click +).
To preview results by collection, search for interview* OR "oral histor*" limited to collections . Revise the search above by adding your topic (for example: artist* ) in the second search box (if you don't see the box, click +). Although this method does not allow you to isolate digitized content, you may find the refinement options on the right side of the screen (refine by repository, subject or names) helpful. Once your select a given collection, you may search within it (e.g., for your topic or the term interview).

UX & MARKET RESEARCH INTERVIEWS

Ux at harvard library .

User Experience and Market Research interviews can inform the design of tangible products and services through responsive, outcome-driven insights. The User Research Center at Harvard Library specializes in this kind of user-centered design, digital accessibility, and testing. They also offer guidance and resources to members of the Harvard Community who are interested in learning more about UX methods. Contact [email protected] or consult the URC website for more information.

Websites

User Interviews: The Beginner’s Guide (Chris Mears)
Interviewing Users (Jakob Nielsen)

Books

Interviewing Users: How to Uncover Compelling Insights by Steve Portigal; Grant McCracken (Foreword by) Interviewing is a foundational user research tool that people assume they already possess. Everyone can ask questions, right? Unfortunately, that's not the case. Interviewing Users provides invaluable interviewing techniques and tools that enable you to conduct informative interviews with anyone. You'll move from simply gathering data to uncovering powerful insights about people.
Rapid Contextual Design by Jessamyn Wendell; Karen Holtzblatt; Shelley Wood This handbook introduces Rapid CD, a fast-paced, adaptive form of Contextual Design. Rapid CD is a hands-on guide for anyone who needs practical guidance on how to use the Contextual Design process and adapt it to tactical projects with tight timelines and resources. Rapid Contextual Design provides detailed suggestions on structuring the project and customer interviews, conducting interviews, and running interpretation sessions. The handbook walks you step-by-step through organizing the data so you can see your key issues, along with visioning new solutions, storyboarding to work out the details, and paper prototype interviewing to iterate the design all with as little as a two-person team with only a few weeks to spare *Includes real project examples with actual customer data that illustrate how a CD project actually works.

Videos

Instructional Presentations on Interview Skills

Interview/Oral History Research for RSRA 298B: Master's Thesis Reading and Research (Spring 2023) Slideshow covers: Why Interviews?, Getting Context, Engaging Participants, Conducting the Interview, The Interview Guide, Note Taking, Transcription, File management, and Data Analysis.
Interview Skills From an online class on February 13, 2023: Get set up for interview research. You will leave prepared to choose among the three types of interviewing methods, equipped to develop an interview schedule, aware of data management options and their ethical implications, and knowledgeable of technologies you can use to record and transcribe your interviews. This workshop complements Intro to NVivo, a qualitative data analysis tool useful for coding interview data.

NIH Data Management & Sharing Policy (DMSP) This policy, effective January 25, 2023, applies to all research, funded or conducted in whole or in part by NIH, that results in the generation of scientific data , including NIH-funded qualitative research. Click here to see some examples of how the DMSP policy has been applied in qualitative research studies featured in the 2021 Qualitative Data Management Plan (DMP) Competition . As a resource for the community, NIH has developed a resource for developing informed consent language in research studies where data and/or biospecimens will be stored and shared for future use. It is important to note that the DMS Policy does NOT require that informed consent obtained from research participants must allow for broad sharing and the future use of data (either with or without identifiable private information). See the FAQ for more information.

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Chapter 13: Interviews

Danielle Berkovic

Learning outcomes

Upon completion of this chapter, you should be able to:

Understand when to use interviews in qualitative research.
Develop interview questions for an interview guide.
Understand how to conduct an interview.

What are interviews?

An interviewing method is the most commonly used data collection technique in qualitative research. 1 The purpose of an interview is to explore the experiences, understandings, opinions and motivations of research participants. 2 Interviews are conducted one-on-one with the researcher and the participant. Interviews are most appropriate when seeking to understand a participant’s subjective view of an experience and are also considered suitable for the exploration of sensitive topics.

What are the different types of interviews?

There are four main types of interviews:

Key stakeholder: A key stakeholder interview aims to explore one issue in detail with a person of interest or importance concerning the research topic. 3 Key stakeholder interviews seek the views of experts on some cultural, political or health aspects of the community, beyond their personal beliefs or actions. An example of a key stakeholder is the Chief Health Officer of Victoria (Australia’s second-most populous state) who oversaw the world’s longest lockdowns in response to the COVID-19 pandemic.
Dyad: A dyad interview aims to explore one issue in a level of detail with a dyad (two people). This form of interviewing is used when one participant of the dyad may need some support or is not wholly able to articulate themselves (e.g. people with cognitive impairment, or children). Independence is acknowledged and the interview is analysed as a unit. 4
Narrative: A narrative interview helps individuals tell their stories, and prioritises their own perspectives and experiences using the language that they prefer. 5 This type of interview has been widely used in social research but is gaining prominence in health research to better understand person-centred care, for example, negotiating exercise and food abstinence whilst living with Type 2 diabetes. 6,7
Life history: A life history interview allows the researcher to explore a person’s individual and subjective experiences within a history of the time framework. 8 Life history interviews challenge the researcher to understand how people’s current attitudes, behaviours and choices are influenced by previous experiences or trauma. Life history interviews have been conducted with Holocaust survivors 9 and youth who have been forcibly recruited to war. 10

Table 13.4 provides a summary of four studies, each adopting one of these types of interviews.

Interviewing techniques

There are two main interview techniques:

Semi-structured: Semi-structured interviewing aims to explore a few issues in moderate detail, to expand the researcher’s knowledge at some level. 11 Semi-structured interviews give the researcher the advantage of remaining reasonably objective while enabling participants to share their perspectives and opinions. The researcher should create an interview guide with targeted open questions to direct the interview. As examples, semi-structured interviews have been used to extend knowledge of why women might gain excess weight during pregnancy, 12 and to update guidelines for statin uptake. 13
In-depth: In-depth interviewing aims to explore a person’s subjective experiences and feelings about a particular topic. 14 In-depth interviews are often used to explore emotive (e.g. end-of-life care) 15 and complex (e.g. adolescent pregnancy) topics. 16 The researcher should create an interview guide with selected open questions to ask of the participant, but the participant should guide the direction of the interview more than in a semi-structured setting. In-depth interviews value participants’ lived experiences and are frequently used in phenomenology studies (as described in Chapter 6) .

When to use the different types of interview s

The type of interview a researcher uses should be determined by the study design, the research aims and objectives, and participant demographics. For example, if conducting a descriptive study, semi-structured interviews may be the best method of data collection. As explained in Chapter 5 , descriptive studies seek to describe phenomena, rather than to explain or interpret the data. A semi-structured interview, which seeks to expand upon some level of existing knowledge, will likely best facilitate this.

Similarly, if conducting a phenomenological study, in-depth interviews may be the best method of data collection. As described in Chapter 6 , the key concept of phenomenology is the individual. The emphasis is on the lived experience of that individual and the person’s sense-making of those experiences. Therefore, an in-depth interview is likely best placed to elicit that rich data.

While some interview types are better suited to certain study designs, there are no restrictions on the type of interview that may be used. For example, semi-structured interviews provide an excellent accompaniment to trial participation (see Chapter 11 about mixed methods), and key stakeholder interviews, as part of an action research study, can be used to define priorities, barriers and enablers to implementation.

How do I write my interview questions?

An interview aims to explore the experiences, understandings, opinions and motivations of research participants. The general rule is that the interviewee should speak for 80 per cent of the interview, and the interviewer should only be asking questions and clarifying responses, for about 20 per cent of the interview. This percentage may differ depending on the interview type; for example, a semi-structured interview involves the researcher asking more questions than in an in-depth interview. Still, to facilitate free-flowing responses, it is important to use open-ended language to encourage participants to be expansive in their responses. Examples of open-ended terms include questions that start with ‘who’, ‘how’ and ‘where’.

The researcher should avoid closed-ended questions that can be answered with yes or no, and limit conversation. For example, asking a participant ‘Did you have this experience?’ can elicit a simple ‘yes’, whereas asking them to ‘Describe your experience’, will likely encourage a narrative response. Table 13.1 provides examples of terminology to include and avoid in developing interview questions.

Table 13.1. Interview question formats to use and avoid

How long should my interview be.

There is no rule about how long an interview should take. Different types of interviews will likely run for different periods of time, but this also depends on the research question/s and the type of participant. For example, given that a semi-structured interview is seeking to expand on some previous knowledge, the interview may need no longer than 30 minutes, or up to one hour. An in-depth interview seeks to explore a topic in a greater level of detail and therefore, at a minimum, would be expected to last an hour. A dyad interview may be as short as 15 minutes (e.g. if the dyad is a person with dementia and a family member or caregiver) or longer, depending on the pairing.

Designing your interview guide

To figure out what questions to ask in an interview guide, the researcher may consult the literature, speak to experts (including people with lived experience) about the research and draw on their current knowledge. The topics and questions should be mapped to the research question/s, and the interview guide should be developed well in advance of commencing data collection. This enables time and opportunity to pilot-test the interview guide. The pilot interview provides an opportunity to explore the language and clarity of questions, the order and flow of the guide and to determine whether the instructions are clear to participants both before and after the interview. It can be beneficial to pilot-test the interview guide with someone who is not familiar with the research topic, to make sure that the language used is easily understood (and will be by participants, too). The study design should be used to determine the number of questions asked and the duration of the interview should guide the extent of the interview guide. The participant type may also determine the extent of the interview guide; for example, clinicians tend to be time-poor and therefore shorter, focused interviews are optimal. An interview guide is also likely to be shorter for a descriptive study than a phenomenological or ethnographic study, given the level of detail required. Chapter 5 outlined a descriptive study in which participants who had undergone percutaneous coronary intervention were interviewed. The interview guide consisted of four main questions and subsequent probing questions, linked to the research questions (see Table 13.2). 17

Table 13.2. Interview guide for a descriptive study

Table 13.3 is an example of a larger and more detailed interview guide, designed for the qualitative component of a mixed-methods study aiming to examine the work and financial effects of living with arthritis as a younger person. The questions are mapped to the World Health Organization’s International Classification of Functioning, Disability, and Health, which measures health and disability at individual and population levels. 18

Table 13.3. Detailed interview guide

It is important to create an interview guide, for the following reasons:

The researcher should be familiar with their research questions.
Using an interview guide will enable the incorporation of feedback from the piloting process.
It is difficult to predict how participants will respond to interview questions. They may answer in a way that is anticipated or they may provide unanticipated insights that warrant follow-up. An interview guide (a physical or digital copy) enables the researcher to note these answers and follow-up with appropriate inquiry.
Participants will likely have provided heterogeneous answers to certain questions. The interview guide enables the researcher to note similarities and differences across various interviews, which may be important in data analysis.
Even experienced qualitative researchers get nervous before an interview! The interview guide provides a safety net if the researcher forgets their questions or needs to anticipate the next question.

Setting up the interview

In the past, most interviews were conducted in person or by telephone. Emerging technologies promote easier access to research participation (e.g. by people living in rural or remote communities, or for people with mobility limitations). Even in metropolitan settings, many interviews are now conducted electronically (e.g. using videoconferencing platforms). Regardless of your interview setting, it is essential that the interview environment is comfortable for the participant. This process can begin as soon as potential participants express interest in your research. Following are some tips from the literature and our own experiences of leading interviews:

Answer questions and set clear expectations . Participating in research is not an everyday task. People do not necessarily know what to expect during a research interview, and this can be daunting. Give people as much information as possible, answer their questions about the research and set clear expectations about what the interview will entail and how long it is expected to last. Let them know that the interview will be recorded for transcription and analysis purposes. Consider sending the interview questions a few days before the interview. This gives people time and space to reflect on their experiences, consider their responses to questions and to provide informed consent for their participation.
Consider your setting . If conducting the interview in person, consider the location and room in which the interview will be held. For example, if in a participant’s home, be mindful of their private space. Ask if you should remove your shoes before entering their home. If they offer refreshments (which in our experience many participants do), accept it with gratitude if possible. These considerations apply beyond the participant’s home; if using a room in an office setting, consider privacy and confidentiality, accessibility and potential for disruption. Consider the temperature as well as the furniture in the room, who may be able to overhear conversations and who may walk past. Similarly, if interviewing by phone or online, take time to assess the space, and if in a house or office that is not quiet or private, use headphones as needed.
Build rapport. The research topic may be important to participants from a professional perspective, or they may have deep emotional connections to the topic of interest. Regardless of the nature of the interview, it is important to remember that participants are being asked to open up to an interviewer who is likely to be a stranger. Spend some time with participants before the interview, to make sure that they are comfortable. Engage in some general conversation, and ask if they have any questions before you start. Remember that it is not a normal part of someone’s day to participate in research. Make it an enjoyable and/or meaningful experience for them, and it will enhance the data that you collect.
Let participants guide you. Oftentimes, the ways in which researchers and participants describe the same phenomena are different. In the interview, reflect the participant’s language. Make sure they feel heard and that they are willing and comfortable to speak openly about their experiences. For example, our research involves talking to older adults about their experience of falls. We noticed early in this research that participants did not use the word ‘fall’ but would rather use terms such as ‘trip’, ‘went over’ and ‘stumbled’. As interviewers we adopted the participant’s language into our questions.
Listen consistently and express interest. An interview is more complex than a simple question-and-answer format. The best interview data comes from participants feeling comfortable and confident to share their stories. By the time you are completing the 20th interview, it can be difficult to maintain the same level of concentration as with the first interview. Try to stay engaged: nod along with your participants, maintain eye contact, murmur in agreement and sympathise where warranted.
The interviewer is both the data collector and the data collection instrument. The data received is only as good as the questions asked. In qualitative research, the researcher influences how participants answer questions. It is important to remain reflexive and aware of how your language, body language and attitude might influence the interview. Being rested and prepared will enhance the quality of the questions asked and hence the data collected.
Avoid excessive use of ‘why’. It can be challenging for participants to recall why they felt a certain way or acted in a particular manner. Try to avoid asking ‘why’ questions too often, and instead adopt some of the open language described earlier in the chapter.

After your interview

When you have completed your interview, thank the participant and let them know they can contact you if they have any questions or follow-up information they would like to provide. If the interview has covered sensitive topics or the participant has become distressed throughout the interview, make sure that appropriate referrals and follow-up are provided (see section 6).

Download the recording from your device and make sure it is saved in a secure location that can only be accessed by people on the approved research team (see Chapters 35 and 36).

It is important to know what to do immediately after each interview is completed. Interviews should be transcribed – that is, reproduced verbatim for data analysis. Transcribing data is an important step in the process of analysis, but it is very time-consuming; transcribing a 60-minute interview can take up to 8 hours. Data analysis is discussed in Section 4.

Table 13.4. Examples of the four types of interviews

Interviews are the most common data collection technique in qualitative research. There are four main types of interviews; the one you choose will depend on your research question, aims and objectives. It is important to formulate open-ended interview questions that are understandable and easy for participants to answer. Key considerations in setting up the interview will enhance the quality of the data obtained and the experience of the interview for the participant and the researcher.

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Qualitative Research – a practical guide for health and social care researchers and practitioners Copyright © 2023 by Danielle Berkovic is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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How to carry out great interviews in qualitative research.

11 min read An interview is one of the most versatile methods used in qualitative research. Here’s what you need to know about conducting great qualitative interviews.

What is a qualitative research interview?

Qualitative research interviews are a mainstay among q ualitative research techniques, and have been in use for decades either as a primary data collection method or as an adjunct to a wider research process. A qualitative research interview is a one-to-one data collection session between a researcher and a participant. Interviews may be carried out face-to-face, over the phone or via video call using a service like Skype or Zoom.

There are three main types of qualitative research interview – structured, unstructured or semi-structured.

Structured interviews Structured interviews are based around a schedule of predetermined questions and talking points that the researcher has developed. At their most rigid, structured interviews may have a precise wording and question order, meaning that they can be replicated across many different interviewers and participants with relatively consistent results.
Unstructured interviews Unstructured interviews have no predetermined format, although that doesn’t mean they’re ad hoc or unplanned. An unstructured interview may outwardly resemble a normal conversation, but the interviewer will in fact be working carefully to make sure the right topics are addressed during the interaction while putting the participant at ease with a natural manner.
Semi-structured interviews Semi-structured interviews are the most common type of qualitative research interview, combining the informality and rapport of an unstructured interview with the consistency and replicability of a structured interview. The researcher will come prepared with questions and topics, but will not need to stick to precise wording. This blended approach can work well for in-depth interviews.

Free eBook: The qualitative research design handbook

What are the pros and cons of interviews in qualitative research?

As a qualitative research method interviewing is hard to beat, with applications in social research, market research, and even basic and clinical pharmacy. But like any aspect of the research process, it’s not without its limitations. Before choosing qualitative interviewing as your research method, it’s worth weighing up the pros and cons.

Pros of qualitative interviews:

provide in-depth information and context
can be used effectively when their are low numbers of participants
provide an opportunity to discuss and explain questions
useful for complex topics
rich in data – in the case of in-person or video interviews , the researcher can observe body language and facial expression as well as the answers to questions

Cons of qualitative interviews:

can be time-consuming to carry out
costly when compared to some other research methods
because of time and cost constraints, they often limit you to a small number of participants
difficult to standardize your data across different researchers and participants unless the interviews are very tightly structured
As the Open University of Hong Kong notes, qualitative interviews may take an emotional toll on interviewers

Qualitative interview guides

Semi-structured interviews are based on a qualitative interview guide, which acts as a road map for the researcher. While conducting interviews, the researcher can use the interview guide to help them stay focused on their research questions and make sure they cover all the topics they intend to.

An interview guide may include a list of questions written out in full, or it may be a set of bullet points grouped around particular topics. It can prompt the interviewer to dig deeper and ask probing questions during the interview if appropriate.

Consider writing out the project’s research question at the top of your interview guide, ahead of the interview questions. This may help you steer the interview in the right direction if it threatens to head off on a tangent.

Avoid bias in qualitative research interviews

According to Duke University , bias can create significant problems in your qualitative interview.

Acquiescence bias is common to many qualitative methods, including focus groups. It occurs when the participant feels obliged to say what they think the researcher wants to hear. This can be especially problematic when there is a perceived power imbalance between participant and interviewer. To counteract this, Duke University’s experts recommend emphasizing the participant’s expertise in the subject being discussed, and the value of their contributions.
Interviewer bias is when the interviewer’s own feelings about the topic come to light through hand gestures, facial expressions or turns of phrase. Duke’s recommendation is to stick to scripted phrases where this is an issue, and to make sure researchers become very familiar with the interview guide or script before conducting interviews, so that they can hone their delivery.

What kinds of questions should you ask in a qualitative interview?

The interview questions you ask need to be carefully considered both before and during the data collection process. As well as considering the topics you’ll cover, you will need to think carefully about the way you ask questions.

Open-ended interview questions – which cannot be answered with a ‘yes’ ‘no’ or ‘maybe’ – are recommended by many researchers as a way to pursue in depth information.

An example of an open-ended question is “What made you want to move to the East Coast?” This will prompt the participant to consider different factors and select at least one. Having thought about it carefully, they may give you more detailed information about their reasoning.

A closed-ended question , such as “Would you recommend your neighborhood to a friend?” can be answered without too much deliberation, and without giving much information about personal thoughts, opinions and feelings.

Follow-up questions can be used to delve deeper into the research topic and to get more detail from open-ended questions. Examples of follow-up questions include:

What makes you say that?
What do you mean by that?
Can you tell me more about X?
What did/does that mean to you?

As well as avoiding closed-ended questions, be wary of leading questions. As with other qualitative research techniques such as surveys or focus groups, these can introduce bias in your data. Leading questions presume a certain point of view shared by the interviewer and participant, and may even suggest a foregone conclusion.

An example of a leading question might be: “You moved to New York in 1990, didn’t you?” In answering the question, the participant is much more likely to agree than disagree. This may be down to acquiescence bias or a belief that the interviewer has checked the information and already knows the correct answer.

Other leading questions involve adjectival phrases or other wording that introduces negative or positive connotations about a particular topic. An example of this kind of leading question is: “Many employees dislike wearing masks to work. How do you feel about this?” It presumes a positive opinion and the participant may be swayed by it, or not want to contradict the interviewer.

Harvard University’s guidelines for qualitative interview research add that you shouldn’t be afraid to ask embarrassing questions – “if you don’t ask, they won’t tell.” Bear in mind though that too much probing around sensitive topics may cause the interview participant to withdraw. The Harvard guidelines recommend leaving sensitive questions til the later stages of the interview when a rapport has been established.

More tips for conducting qualitative interviews

Observing a participant’s body language can give you important data about their thoughts and feelings. It can also help you decide when to broach a topic, and whether to use a follow-up question or return to the subject later in the interview.

Be conscious that the participant may regard you as the expert, not themselves. In order to make sure they express their opinions openly, use active listening skills like verbal encouragement and paraphrasing and clarifying their meaning to show how much you value what they are saying.

Remember that part of the goal is to leave the interview participant feeling good about volunteering their time and their thought process to your research. Aim to make them feel empowered , respected and heard.

Unstructured interviews can demand a lot of a researcher, both cognitively and emotionally. Be sure to leave time in between in-depth interviews when scheduling your data collection to make sure you maintain the quality of your data, as well as your own well-being .

Recording and transcribing interviews

Historically, recording qualitative research interviews and then transcribing the conversation manually would have represented a significant part of the cost and time involved in research projects that collect qualitative data.

Fortunately, researchers now have access to digital recording tools, and even speech-to-text technology that can automatically transcribe interview data using AI and machine learning. This type of tool can also be used to capture qualitative data from qualitative research (focus groups,ect.) making this kind of social research or market research much less time consuming.

Data analysis

Qualitative interview data is unstructured, rich in content and difficult to analyze without the appropriate tools. Fortunately, machine learning and AI can once again make things faster and easier when you use qualitative methods like the research interview.

Text analysis tools and natural language processing software can ‘read’ your transcripts and voice data and identify patterns and trends across large volumes of text or speech. They can also perform khttps://www.qualtrics.com/experience-management/research/sentiment-analysis/

which assesses overall trends in opinion and provides an unbiased overall summary of how participants are feeling.

Another feature of text analysis tools is their ability to categorize information by topic, sorting it into groupings that help you organize your data according to the topic discussed.

All in all, interviews are a valuable technique for qualitative research in business, yielding rich and detailed unstructured data. Historically, they have only been limited by the human capacity to interpret and communicate results and conclusions, which demands considerable time and skill.

When you combine this data with AI tools that can interpret it quickly and automatically, it becomes easy to analyze and structure, dovetailing perfectly with your other business data. An additional benefit of natural language analysis tools is that they are free of subjective biases, and can replicate the same approach across as much data as you choose. By combining human research skills with machine analysis, qualitative research methods such as interviews are more valuable than ever to your business.

Related resources

Market intelligence 10 min read, marketing insights 11 min read, ethnographic research 11 min read, qualitative vs quantitative research 13 min read, qualitative research questions 11 min read, qualitative research design 12 min read, primary vs secondary research 14 min read, request demo.

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How to Conduct Interviews in Qualitative Research: Interview Guidelines for Qualitative Research

Rev › Blog › Market Research › How to Conduct Interviews in Qualitative Research: Interview Guidelines for Qualitative Research

Qualitative research interviews are depth interviews. They elicit detailed feedback from your leads and customers. Unstructured interviews reveal why people react in a certain way or make certain decisions. According to The Hartford , qualitative research provides an anecdotal look into your business. That provides an important form of data.

Why Your Business Should Use a Qualitative Interview Process

Qualitative research helps business owners:

Identify customer needs
Clarify marketing messages
Generate ideas for improvements of a product
Decide to extend a line or brand
Gain perspective on how a product fits into a customer’s lifestyle

How Is Conducting Qualitative Research & Quantitative Research Different?

Quantitative research concerns measurable quantities and numbers. It involves close-ended questions. Answer possibilities include yes or no, true or false, or various set choices. Qualitative research is descriptive and concerned with understanding behavior. It invites people to tell their stories in their own words.

Examples of Qualitative Research

Qualitative research helps researchers understand the social reality of individuals, groups and cultures. Qualitative research for businesses involves understanding consumer behavior. It can involve ethnographic techniques, including participant observation and field research. It also includes phenomenology, understanding life experiences using written or recorded narratives. Qualitative research also includes in-depth interviews.

What Is a Qualitative Interview?

A qualitative interview is a more personal form of research compared to questionnaires. The interviewer can probe or ask follow-up research questions of the interview participant. In some cases, subjects may start to interview the interviewer. This fosters deep discussion of the interview topic.

Why Are Interview Techniques in Qualitative Research Effective?

Qualitative research interviews help you explain, understand and explore opinions, behavior and experiences. Qualitative research can provide insights into a phenomenon. Qualitative research discoveries can be further researched and analyzed to influence business decisions.

How Are Interviews in Qualitative Research Formatted?

Qualitative research interviews may take place one-on-one or in focus groups. Learn how to run a successful focus group . Interviews span around 30 to 90 minutes. The interview can take place in person, over the phone or through video chat. The interviewer collects information about opinions, behavior, attitudes, feelings, preferences and knowledge.

How to Conduct Interviews in Qualitative Research

1. determine your goal., 2. target people to interview., 3. design interview questions., 4. prep the interview., 5. conduct the interview., 6. transcribe and analyze the interview., 7. optimize and evolve your interview guide., the first step in qualitative research: determine your goal.

Determine what you want to study:

A current or potential product, service or brand positioning
Strengths and weaknesses in products
Purchasing decisions
Reactions to advertising or marketing campaigns
Usability of a website or other interactive services
Perceptions about the company, brand or product
Reactions to packaging and design

How Can You Decide a Goal for a Qualitative Interview?

Have your business team ask the following questions:

What information do you want to get?
Why do you want to pursue in-depth information about this research topic?
Why is a qualitative interview process the best solution for this research?
How will you use qualitative data to improve your business?

How to Determine the Right Interview Participants

When looking for people to talk to for a qualitative interview, consider your goal. If you want to expand a product line, interview existing customers about their needs. If you’re researching marketing, ask new customers how they found your business. Match interview subjects with the goal of the interview.

How to Design Interview Questions for Qualitative Research

When you’re creating an interview guide, it’s a good idea to:

Plan structured interviews with open ended questions.
Avoid leading questions.
Create interview questions that are clear and easy to understand.
Make research questions focused but flexible.
Design questions that align with data collection and data analysis goals.

Tips for Preparing a Qualitative Research Interview

Preparation improves interview effectiveness. Tips to prepare include:

Create an interview guide. The guide should include questions, question intent and answer-based paths to take.
Choose a setting where the subject feels comfortable.
Build rapport with interview participants.
Have a reliable way to record the interview.
Rehearse the interview first.

Environmental Concerns for Qualitative Interviews

The setting of a qualitative interview also affects the quality of the interview. Consider the needs of the subject. For example, if you’re interviewing a teenager, a formal boardroom may not be the best setting. Some cultures may not value direct eye contact. An interview that’s non-face-to-face may be better.

How to Make Qualitative Interview Subjects Comfortable

For long interviews, offer water and breaks to participants. Be polite and respectful when interacting with interview subjects. Let interview participants know the purpose of the research. Explain exactly how you’ll use their answers. Address terms of confidentiality if necessary. Thank participants after the interview and let them know what to expect next.

What Are Interview Techniques in Qualitative Research?

Qualitative research techniques include:

Start interviews with “get-to-know-you” questions to put the interview participant at ease.
Pay attention.
Use active listening techniques.
Watch for body language cues.
Pivot questions as needed.
Acknowledge emotions.
Avoid interrogation.
Ending interviews, ask subjects if they have anything to add.

What Is Active Listening in Interviews in Qualitative Research?

Active listening techniques include:

Make eye contact.
Lean in and use body language to show you’re listening.
Don’t get distracted by devices.
Use verbal affirmation.
Paraphrase answers for reflection.
Reference earlier answers.
Avoid interrupting.
Embrace pauses.
Ask for clarification.
Pay attention in the moment.

Tips for Transcribing a Qualitative Interview

It’s best to transcribe and analyze a qualitative research interview right away. This helps you optimize future interviews. Transcribe the interview word for word. Note non-verbal interactions in your transcription. Interactions like pauses and laughter can provide deeper insights into responses.

How to Analyze a Qualitative Interview

Analyze your qualitative research data early. That way, you can identify emerging themes to shape future interviews. Consider adding these to each interview report:

The goal of the interview
Details about the interview participant
Questions asked, summarized responses and key findings
Recommendations

Relate the analysis to the goal of the qualitative research interview.

Optimize the Interview Guide for Qualitative Research

Each interview can help you improve the efficiency and effectiveness of future ones. Adjust your interview guide based on insights from each previous interview. Keep all versions of your transcriptions and interview guides with notes on them. You can reference these for future qualitative research.

Get Reliable Transcription Services for Qualitative Research Interviews

As mentioned, you should transcribe qualitative research interviews as soon as possible. There are several reasons for this.

You can gain insights that help you shape your interview guide. You might identify questions to add or questions to clarify.
Your interview participants may not be appropriate for this type of qualitative research. Finding more targeted interview subjects may be better.
Answers may evolve the qualitative research goal and/or data analysis.

At Rev, we understand the need for fast transcription for accurate market research. We provide a turnaround time of as few as 12 hours, no matter how big your project is. We guarantee 99%+ accuracy. Learn about Rev’s market research transcription . We can help make your qualitative research project a success.

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Qualitative Interview: What it is & How to conduct one

A qualitative interview is commonly used in research projects involving new products, brand positioning, purchase dynamics, market research, social research, behavioral analysis, exploring market segments, etc. Recent data also suggests that it is highly effective when used in employee engagement initiatives.

It has also proven to be extremely helpful when it comes to problem definition as well as developing an approach to a particular problem.

What is a Qualitative Interview?

A qualitative Interview is a research approach used in a qualitative study where more personal interaction is required and detailed in depth information is gathered from the participant. Qualitative interviews usually involve follow-up questions and are conducted in a conversation or discussion format.

A qualitative interview is a more personal form of research agenda compared to general questionnaires or focused group studies. Such formats often include open-ended and follow-up questions .

LEARN ABOUT: Behavioral Research

How to conduct a Qualitative Interview?

Conducting a qualitative interview requires careful planning and implementation to ensure that you gather meaningful and rich data. Here are some steps to consider when conducting a qualitative research interview:

Clearly define the purpose of your qualitative interview and the specific research method questions you want to address. It will help you design appropriate research interview questions and interview guides for your data analysis.

Identify the target population or specific individuals who can provide valuable insights related to your research questions. Consider criteria such as demographics, expertise, or experiences that align with your research methods and objectives. Use appropriate methods, such as purposive sampling of data collection, to recruit participants who can offer diverse perspectives.

Before conducting the interview, ensure that participants understand the purpose, procedures, and potential risks or benefits of their involvement. Obtain their informed consent, clearly explaining their rights as participants, including confidentiality and their ability to withdraw from the study at any time.

Prepare a flexible in depth interviews guide that includes a set of open-ended interview questions for an interview participant. The guide should be designed to elicit participants’ perspectives, experiences, and insights related to your research objectives for conducting interviews. Consider using probing techniques to encourage participants to elaborate on their responses and explore different dimensions of the topic.

Select a suitable location for the in depth interviews that is comfortable, private, and free from distractions for an interview participant. Create a relaxed and welcoming atmosphere to help participants feel at ease and encourage open communication for qualitative interviewing. Establish rapport and build trust with participants by introducing yourself, explaining the purpose of conducting interviews, and actively listening to their responses.

Start by asking introductory questions to establish a rapport with the participant. Follow the qualitative interview guide, but remain flexible and responsive to participants’ responses. Allow participants to speak freely and provide detailed answers, using probing techniques to delve deeper into their experiences, emotions, and perspectives. Take notes or record the interview (with participants’ consent) to capture accurate and detailed information.

Show respect for their experiences and perspectives, even if they differ from yours. Avoid making judgments or imposing your own beliefs during the interview. Create a non-judgmental and inclusive environment that encourages participants to share their thoughts and feelings honestly.

Transcribe the interview recordings or review your notes promptly after each interview while the details remain fresh. Analyze the qualitative data using appropriate methods, such as thematic data analysis, to identify patterns, themes, and insights. Ensure that the data is anonymized and handled following ethical guidelines.

By following these steps, you can conduct a qualitative research interview that facilitates rich and meaningful discussions, resulting in valuable data analysis for your research process.

LEARN ABOUT: Research Process Steps

Types of Qualitative Interviews

The interview itself can be conducted over multiple formats. Qualitative researchers can employ several types of qualitative interviews based on their research objectives and the nature of the study. Here are some popular types of qualitative interviews:

Structured interviews involve a predetermined set of questions that are asked in the same order and manner to each participant. The questions of structured interviews are typically closed-ended or have limited response options. This type of interview is proper when researchers aim to collect specific information in a standardized way, allowing for easier comparison and analysis of responses across participants.

Semi-structured interviews combine predetermined questions with flexibility for additional probing and follow-up questions. Researchers have a set of core questions to guide the interview but can adapt the interview data collection process based on participants’ responses. This type of approach allows for a deeper exploration of participants’ experiences, thoughts, and perspectives while maintaining some standardization level.

Unstructured interviews involve open-ended questions and a free-flowing conversation between the interviewer and the participant. The interviewer may have a general topic or area of interest but allows the conversation to evolve naturally. Unstructured interviews provide a high degree of flexibility and allow participants to express themselves more freely, often leading to rich and nuanced data.

Each qualitative interview type has its strengths and is suited for different research purposes. Researchers or a research team should carefully select the appropriate type of research interview that aligns with their research objectives, the nature of the phenomenon under investigation, and the population being studied.

LEARN ABOUT: Structured Question

Advantages of Using Qualitative Interviews

Qualitative interview techniques offer several advantages as a research method. Here are some of the key advantages:

A qualitative interview allows researchers to delve deeply into participants’ experiences, perspectives, and opinions. Using open-ended questions and probing techniques, researchers can uncover rich and detailed information beyond mere surface-level responses. This in-depth exploration provides a comprehensive understanding of the research topic.

Qualitative interviews offer flexibility in adapting the interview data collection process to the specific needs of each participant. Researchers can tailor their questions, follow-up probes, and overall approach based on the participant’s responses, allowing for a more personalized and engaging research experience. This flexibility enhances the quality and richness of the data collection.

Qualitative interview prioritizes the voices and perspectives of participants. Through interactive and conversational exchanges, participants can express their thoughts, emotions, and beliefs in their own words. This approach ensures that the research captures individuals’ nuanced and diverse experiences, offering insights that may not be obtained through other methods.

A qualitative research interview provides a holistic understanding of the social and cultural context surrounding participants’ experiences. Researchers can explore the factors influencing participants’ perspectives, such as cultural norms, societal expectations, or personal histories. This contextual understanding enhances the interpretation and analysis of the data, providing a comprehensive view of the research topic.

Qualitative interviews are particularly effective when studying sensitive or complex topics. It allows participants to share their experiences and emotions in a safe and confidential environment, facilitating a deeper exploration of potentially challenging subjects. This method also enables researchers to capture these topics’ nuances, contradictions, and subtleties, contributing to a more comprehensive understanding.

Qualitative research interviews can empower participants by giving them a voice and acknowledging the value of their experiences. By actively listening and engaging in meaningful dialogue, researchers validate participants’ contributions and foster a sense of ownership over their narratives. This empowerment can positively affect participants’ self-esteem, self-reflection, and personal growth.

Overall, qualitative interview provides researchers with a powerful tool to explore complex phenomena, gain in-depth insights, and understand the subjective experiences of individuals. By capitalizing on the advantages of this method, researchers can generate valuable and nuanced data that contributes to the advancement of knowledge in their respective fields.

Learn more by reading our guide: Types of Interviews .

Disadvantages of a Qualitative Interview

While a qualitative interview has many advantages, it is essential to acknowledge their potential limitations. Here are some of the disadvantages associated with qualitative interviews:

Qualitative interviews involve interaction between the researcher and participants, which introduces the possibility of subjective interpretations and biases. Researchers may unintentionally influence participants’ responses through questioning techniques, non-verbal cues, or personal beliefs. Researchers must be aware of their biases and take steps to minimize their impact on data collection and analysis.

The findings from qualitative research interviews are typically based on small sample size and specific context, making it difficult to generalize the results to a larger population. While qualitative research aims to provide an in-depth understanding, it may need more statistical representativeness than quantitative research methods offer. Therefore, when applying qualitative interview findings to broader populations or contexts, caution must be exercised.

Qualitative interviews can be time-consuming and require substantial resources. Conducting in depth interviews, transcribing data, and analyzing the qualitative data are labor-intensive tasks that require significant time and effort. Researchers must be prepared for qualitative interviews of a detailed and time-consuming nature, especially when working with large or diverse participant samples.

Ensuring the validity and reliability of qualitative research interviews can be challenging. Validity refers to the extent to which the interview data accurately represent participants’ experiences and perspectives, while reliability relates to the consistency and replicability of the findings. Factors such as interviewer bias, participant recall, and social desirability may compromise the validity and reliability of the data. Researchers must employ rigorous methodologies, triangulate data from multiple sources, and establish trustworthiness to enhance the credibility of their findings.

Qualitative interviews capture participants’ experiences and perspectives at a specific time and within a particular context. However, these experiences may evolve or change over time or in different contexts. Researchers must be mindful of the limitations of capturing participants’ experiences, recognizing that their findings may only partially represent the dynamic nature of human behavior and perceptions.

Despite these disadvantages, qualitative interviews remain a valuable research method that offers unique insights into individuals’ experiences and perspectives.

Learn About: Steps in qualitative Research

Qualitative interviews are valuable for gaining in-depth insights into individuals’ experiences, perspectives, and behaviors. They offer a unique opportunity to explore complex phenomena, uncover rich narratives, and understand the underlying meanings and interpretations that individuals assign to their experiences.

To summarize, Qualitative Research can either be a valuable tool to discover problems or help elevate any research programs with subjective data or leave researchers with amorphous and contradictory data. The key is to use the approach in combination with other qualitative and quantitative research techniques to enhance the depth of the data gathered.

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What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on June 19, 2020 by Pritha Bhandari . Revised on June 22, 2023.

Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research , which involves collecting and analyzing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, history, etc.

How does social media shape body image in teenagers?
How do children and adults interpret healthy eating in the UK?
What factors influence employee retention in a large organization?
How is anxiety experienced around the world?
How can teachers integrate social issues into science curriculums?

Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, other interesting articles, frequently asked questions about qualitative research.

Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.

Common approaches include grounded theory, ethnography , action research , phenomenological research, and narrative research. They share some similarities, but emphasize different aims and perspectives.

Note that qualitative research is at risk for certain research biases including the Hawthorne effect , observer bias , recall bias , and social desirability bias . While not always totally avoidable, awareness of potential biases as you collect and analyze your data can prevent them from impacting your work too much.

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Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:

Observations: recording what you have seen, heard, or encountered in detailed field notes.
Interviews: personally asking people questions in one-on-one conversations.
Focus groups: asking questions and generating discussion among a group of people.
Surveys : distributing questionnaires with open-ended questions.
Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
You take field notes with observations and reflect on your own experiences of the company culture.
You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.

Qualitative researchers often consider themselves “instruments” in research because all observations, interpretations and analyses are filtered through their own personal lens.

For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analyzing the data.

Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

Prepare and organize your data. This may mean transcribing interviews or typing up fieldnotes.
Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorize your data.
Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
Identify recurring themes. Link codes together into cohesive, overarching themes.

There are several specific approaches to analyzing qualitative data. Although these methods share similar processes, they emphasize different concepts.

Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:

Flexibility

The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.

Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.

Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.

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Researchers must consider practical and theoretical limitations in analyzing and interpreting their data. Qualitative research suffers from:

Unreliability

The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.

Subjectivity

Due to the researcher’s primary role in analyzing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.

Limited generalizability

Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalizable conclusions because the data may be biased and unrepresentative of the wider population .

Labor-intensive

Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Chi square goodness of fit test
Degrees of freedom
Null hypothesis
Discourse analysis
Control groups
Mixed methods research
Non-probability sampling
Quantitative research
Inclusion and exclusion criteria

Research bias

Rosenthal effect
Implicit bias
Cognitive bias
Selection bias
Negativity bias
Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

There are five common approaches to qualitative research :

Grounded theory involves collecting data in order to develop new theories.
Ethnography involves immersing yourself in a group or organization to understand its culture.
Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
Phenomenological research involves investigating phenomena through people’s lived experiences.
Action research links theory and practice in several cycles to drive innovative changes.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

Prepare and organize your data.
Review and explore your data.
Develop a data coding system.
Assign codes to the data.
Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

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Choosing the Right Setting for a Qualitative Research Interview

Updated on: October 2, 2023

Conducting a qualitative interview outside a recording studio – for e.g. at a cafe, pub, or the interviewee’s house – can be challenging.

It therefore makes sense to spend some time thinking about the kind of setting you want to choose because it can affect the quality of responses you get as well as the quality of the recording you make. In this article, we look at a few ways you can ensure that you pick the correct setting for your qualitative interview and get the best results.

Choose a quiet location

A quiet room is best for conducting a a qualitative interview.

If the outdoors are unavoidable, such as a restaurant or a park, choose a place that’s not too crowded.

At outdoor locations, check for distracting sounds like passing traffic, children playing or loud background music – all of these tend to break the interviewee’s chain of thought.

Recording tip: If you’re recording an interview at an outdoor location, surrounding noise like the sound of clinking cutlery or the wind can drown the voices of the participants. Use professional recording gear like a good digital voice recorder ( see a list of good ones here ) and microphones to ensure a good quality recording.

Choosing-the-right-setting-for-a-qualitative-research-interview-700x675

Minimize distractions

Put cellphones on silent mode, put a ‘Do-not-disturb’ sign on the door and tell people you are not be interrupted. Send the dog for a walk if necessary.

If you’re conducting the qualitative interview at the interviewee’s house or over the phone, convey to the interviewee the importance of an uninterrupted conversation and suggest ways to minimize distractions.

Conduct the interview in a relaxed environment

For a meaningful conversation to take place, it’s important for the interviewee to be at ease.

Choose a location that is comfortable, with no loud noise or light.

If possible, ask the interviewee where they’d like to be interviewed. Some people are comfortable being interviewed at home, others prefer the outdoors or a telephonic interview.

Set up the recording gear before the interview

Beginning on schedule is important. So connect any DVRs/cameras, plug in external microphones and set up your laptop well in advance.

Read: Best Voice Recorders for Interviews and Lectures

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'It's Powerful' The impact of involving children and young people in developing paediatric research agendas: A qualitative interview study

Affiliation.

1 Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
PMID: 38613790
PMCID: PMC11015888
DOI: 10.1111/hex.14028

Introduction: There is a growing consensus that children and young people (CYP) should be involved in matters that concern them. Progress is made in involving CYP in developing pediatric research agendas (PRAs), although the impact of their involvement remains unknown. We aimed to evaluate the impact of involving CYP in developing PRAs and assess the extent to which postpatient and public involvement (post-PPI) activities were planned.

Methods: We conducted a qualitative study using in-depth interviews to identify and gain an in-depth understanding of the impact of involving CYP in developing PRAs. The transcripts were uploaded to Atlas.ti to be coded and organised. Dutch-language interviews were analysed and interpreted together with vocational education and training (VET) students. These students were aged between 14 and 18 years and were training to become nurses.

Results: Three CYP and 15 researchers decided to participate. We focused on three categories of impact: agenda-setting impact, individual impact and academic impact. Involving CYP creates a more enriched and clarified agenda. It ensured that both CYP and researchers underwent personal or professional growth and development, it created a connection between the people involved, awareness about the importance of involving CYP and it ensured that the people involved had a positive experience. The participants were unable to indicate the academic impact of their PRAs, but they did understand the key factors for creating it. In addition, the need to measure impact was highlighted, with a particular focus on assessing individual impact.

Discussion: Our study outlines the diverse subthemes of impact that arise from involving CYP in developing PRAs. Despite the potential of research agendas to amplify CYP voices, only a minority of researchers strategized post-PPI activities ensuring impactful outcomes, prompting the need for thorough evaluation of various impact forms and consistent alignment with the overarching goal of transforming the research field.

Patient or public contribution: We involved VET students in the data analysis and interpretation phase by forming a young person advisory group. The data analysis of the interviews analysed by the VET students revealed four distinct themes: 1. Learnt new knowledge. 2. Learnt to collaborate. 3. Learnt to listen. 4. Assessment of the individual impact.

Keywords: agenda setting impact; children; child‐inclusive research; co‐researchers; impact; paediatric research agenda; priority setting partnerships.

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What is Qualitative in Qualitative Research

Patrik aspers.

1 Department of Sociology, Uppsala University, Uppsala, Sweden

2 Seminar for Sociology, Universität St. Gallen, St. Gallen, Switzerland

3 Department of Media and Social Sciences, University of Stavanger, Stavanger, Norway

What is qualitative research? If we look for a precise definition of qualitative research, and specifically for one that addresses its distinctive feature of being “qualitative,” the literature is meager. In this article we systematically search, identify and analyze a sample of 89 sources using or attempting to define the term “qualitative.” Then, drawing on ideas we find scattered across existing work, and based on Becker’s classic study of marijuana consumption, we formulate and illustrate a definition that tries to capture its core elements. We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. This formulation is developed as a tool to help improve research designs while stressing that a qualitative dimension is present in quantitative work as well. Additionally, it can facilitate teaching, communication between researchers, diminish the gap between qualitative and quantitative researchers, help to address critiques of qualitative methods, and be used as a standard of evaluation of qualitative research.

If we assume that there is something called qualitative research, what exactly is this qualitative feature? And how could we evaluate qualitative research as good or not? Is it fundamentally different from quantitative research? In practice, most active qualitative researchers working with empirical material intuitively know what is involved in doing qualitative research, yet perhaps surprisingly, a clear definition addressing its key feature is still missing.

To address the question of what is qualitative we turn to the accounts of “qualitative research” in textbooks and also in empirical work. In his classic, explorative, interview study of deviance Howard Becker ( 1963 ) asks ‘How does one become a marijuana user?’ In contrast to pre-dispositional and psychological-individualistic theories of deviant behavior, Becker’s inherently social explanation contends that becoming a user of this substance is the result of a three-phase sequential learning process. First, potential users need to learn how to smoke it properly to produce the “correct” effects. If not, they are likely to stop experimenting with it. Second, they need to discover the effects associated with it; in other words, to get “high,” individuals not only have to experience what the drug does, but also to become aware that those sensations are related to using it. Third, they require learning to savor the feelings related to its consumption – to develop an acquired taste. Becker, who played music himself, gets close to the phenomenon by observing, taking part, and by talking to people consuming the drug: “half of the fifty interviews were conducted with musicians, the other half covered a wide range of people, including laborers, machinists, and people in the professions” (Becker 1963 :56).

Another central aspect derived through the common-to-all-research interplay between induction and deduction (Becker 2017 ), is that during the course of his research Becker adds scientifically meaningful new distinctions in the form of three phases—distinctions, or findings if you will, that strongly affect the course of his research: its focus, the material that he collects, and which eventually impact his findings. Each phase typically unfolds through social interaction, and often with input from experienced users in “a sequence of social experiences during which the person acquires a conception of the meaning of the behavior, and perceptions and judgments of objects and situations, all of which make the activity possible and desirable” (Becker 1963 :235). In this study the increased understanding of smoking dope is a result of a combination of the meaning of the actors, and the conceptual distinctions that Becker introduces based on the views expressed by his respondents. Understanding is the result of research and is due to an iterative process in which data, concepts and evidence are connected with one another (Becker 2017 ).

Indeed, there are many definitions of qualitative research, but if we look for a definition that addresses its distinctive feature of being “qualitative,” the literature across the broad field of social science is meager. The main reason behind this article lies in the paradox, which, to put it bluntly, is that researchers act as if they know what it is, but they cannot formulate a coherent definition. Sociologists and others will of course continue to conduct good studies that show the relevance and value of qualitative research addressing scientific and practical problems in society. However, our paper is grounded in the idea that providing a clear definition will help us improve the work that we do. Among researchers who practice qualitative research there is clearly much knowledge. We suggest that a definition makes this knowledge more explicit. If the first rationale for writing this paper refers to the “internal” aim of improving qualitative research, the second refers to the increased “external” pressure that especially many qualitative researchers feel; pressure that comes both from society as well as from other scientific approaches. There is a strong core in qualitative research, and leading researchers tend to agree on what it is and how it is done. Our critique is not directed at the practice of qualitative research, but we do claim that the type of systematic work we do has not yet been done, and that it is useful to improve the field and its status in relation to quantitative research.

The literature on the “internal” aim of improving, or at least clarifying qualitative research is large, and we do not claim to be the first to notice the vagueness of the term “qualitative” (Strauss and Corbin 1998 ). Also, others have noted that there is no single definition of it (Long and Godfrey 2004 :182), that there are many different views on qualitative research (Denzin and Lincoln 2003 :11; Jovanović 2011 :3), and that more generally, we need to define its meaning (Best 2004 :54). Strauss and Corbin ( 1998 ), for example, as well as Nelson et al. (1992:2 cited in Denzin and Lincoln 2003 :11), and Flick ( 2007 :ix–x), have recognized that the term is problematic: “Actually, the term ‘qualitative research’ is confusing because it can mean different things to different people” (Strauss and Corbin 1998 :10–11). Hammersley has discussed the possibility of addressing the problem, but states that “the task of providing an account of the distinctive features of qualitative research is far from straightforward” ( 2013 :2). This confusion, as he has recently further argued (Hammersley 2018 ), is also salient in relation to ethnography where different philosophical and methodological approaches lead to a lack of agreement about what it means.

Others (e.g. Hammersley 2018 ; Fine and Hancock 2017 ) have also identified the treat to qualitative research that comes from external forces, seen from the point of view of “qualitative research.” This threat can be further divided into that which comes from inside academia, such as the critique voiced by “quantitative research” and outside of academia, including, for example, New Public Management. Hammersley ( 2018 ), zooming in on one type of qualitative research, ethnography, has argued that it is under treat. Similarly to Fine ( 2003 ), and before him Gans ( 1999 ), he writes that ethnography’ has acquired a range of meanings, and comes in many different versions, these often reflecting sharply divergent epistemological orientations. And already more than twenty years ago while reviewing Denzin and Lincoln’ s Handbook of Qualitative Methods Fine argued:

While this increasing centrality [of qualitative research] might lead one to believe that consensual standards have developed, this belief would be misleading. As the methodology becomes more widely accepted, querulous challengers have raised fundamental questions that collectively have undercut the traditional models of how qualitative research is to be fashioned and presented (1995:417).

According to Hammersley, there are today “serious treats to the practice of ethnographic work, on almost any definition” ( 2018 :1). He lists five external treats: (1) that social research must be accountable and able to show its impact on society; (2) the current emphasis on “big data” and the emphasis on quantitative data and evidence; (3) the labor market pressure in academia that leaves less time for fieldwork (see also Fine and Hancock 2017 ); (4) problems of access to fields; and (5) the increased ethical scrutiny of projects, to which ethnography is particularly exposed. Hammersley discusses some more or less insufficient existing definitions of ethnography.

The current situation, as Hammersley and others note—and in relation not only to ethnography but also qualitative research in general, and as our empirical study shows—is not just unsatisfactory, it may even be harmful for the entire field of qualitative research, and does not help social science at large. We suggest that the lack of clarity of qualitative research is a real problem that must be addressed.

Towards a Definition of Qualitative Research

Seen in an historical light, what is today called qualitative, or sometimes ethnographic, interpretative research – or a number of other terms – has more or less always existed. At the time the founders of sociology – Simmel, Weber, Durkheim and, before them, Marx – were writing, and during the era of the Methodenstreit (“dispute about methods”) in which the German historical school emphasized scientific methods (cf. Swedberg 1990 ), we can at least speak of qualitative forerunners.

Perhaps the most extended discussion of what later became known as qualitative methods in a classic work is Bronisław Malinowski’s ( 1922 ) Argonauts in the Western Pacific , although even this study does not explicitly address the meaning of “qualitative.” In Weber’s ([1921–-22] 1978) work we find a tension between scientific explanations that are based on observation and quantification and interpretative research (see also Lazarsfeld and Barton 1982 ).

If we look through major sociology journals like the American Sociological Review , American Journal of Sociology , or Social Forces we will not find the term qualitative sociology before the 1970s. And certainly before then much of what we consider qualitative classics in sociology, like Becker’ study ( 1963 ), had already been produced. Indeed, the Chicago School often combined qualitative and quantitative data within the same study (Fine 1995 ). Our point being that before a disciplinary self-awareness the term quantitative preceded qualitative, and the articulation of the former was a political move to claim scientific status (Denzin and Lincoln 2005 ). In the US the World War II seem to have sparked a critique of sociological work, including “qualitative work,” that did not follow the scientific canon (Rawls 2018 ), which was underpinned by a scientifically oriented and value free philosophy of science. As a result the attempts and practice of integrating qualitative and quantitative sociology at Chicago lost ground to sociology that was more oriented to surveys and quantitative work at Columbia under Merton-Lazarsfeld. The quantitative tradition was also able to present textbooks (Lundberg 1951 ) that facilitated the use this approach and its “methods.” The practices of the qualitative tradition, by and large, remained tacit or was part of the mentoring transferred from the renowned masters to their students.

This glimpse into history leads us back to the lack of a coherent account condensed in a definition of qualitative research. Many of the attempts to define the term do not meet the requirements of a proper definition: A definition should be clear, avoid tautology, demarcate its domain in relation to the environment, and ideally only use words in its definiens that themselves are not in need of definition (Hempel 1966 ). A definition can enhance precision and thus clarity by identifying the core of the phenomenon. Preferably, a definition should be short. The typical definition we have found, however, is an ostensive definition, which indicates what qualitative research is about without informing us about what it actually is :

Qualitative research is multimethod in focus, involving an interpretative, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Qualitative research involves the studied use and collection of a variety of empirical materials – case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts – that describe routine and problematic moments and meanings in individuals’ lives. (Denzin and Lincoln 2005 :2)

Flick claims that the label “qualitative research” is indeed used as an umbrella for a number of approaches ( 2007 :2–4; 2002 :6), and it is not difficult to identify research fitting this designation. Moreover, whatever it is, it has grown dramatically over the past five decades. In addition, courses have been developed, methods have flourished, arguments about its future have been advanced (for example, Denzin and Lincoln 1994) and criticized (for example, Snow and Morrill 1995 ), and dedicated journals and books have mushroomed. Most social scientists have a clear idea of research and how it differs from journalism, politics and other activities. But the question of what is qualitative in qualitative research is either eluded or eschewed.

We maintain that this lacuna hinders systematic knowledge production based on qualitative research. Paul Lazarsfeld noted the lack of “codification” as early as 1955 when he reviewed 100 qualitative studies in order to offer a codification of the practices (Lazarsfeld and Barton 1982 :239). Since then many texts on “qualitative research” and its methods have been published, including recent attempts (Goertz and Mahoney 2012 ) similar to Lazarsfeld’s. These studies have tried to extract what is qualitative by looking at the large number of empirical “qualitative” studies. Our novel strategy complements these endeavors by taking another approach and looking at the attempts to codify these practices in the form of a definition, as well as to a minor extent take Becker’s study as an exemplar of what qualitative researchers actually do, and what the characteristic of being ‘qualitative’ denotes and implies. We claim that qualitative researchers, if there is such a thing as “qualitative research,” should be able to codify their practices in a condensed, yet general way expressed in language.

Lingering problems of “generalizability” and “how many cases do I need” (Small 2009 ) are blocking advancement – in this line of work qualitative approaches are said to differ considerably from quantitative ones, while some of the former unsuccessfully mimic principles related to the latter (Small 2009 ). Additionally, quantitative researchers sometimes unfairly criticize the first based on their own quality criteria. Scholars like Goertz and Mahoney ( 2012 ) have successfully focused on the different norms and practices beyond what they argue are essentially two different cultures: those working with either qualitative or quantitative methods. Instead, similarly to Becker ( 2017 ) who has recently questioned the usefulness of the distinction between qualitative and quantitative research, we focus on similarities.

The current situation also impedes both students and researchers in focusing their studies and understanding each other’s work (Lazarsfeld and Barton 1982 :239). A third consequence is providing an opening for critiques by scholars operating within different traditions (Valsiner 2000 :101). A fourth issue is that the “implicit use of methods in qualitative research makes the field far less standardized than the quantitative paradigm” (Goertz and Mahoney 2012 :9). Relatedly, the National Science Foundation in the US organized two workshops in 2004 and 2005 to address the scientific foundations of qualitative research involving strategies to improve it and to develop standards of evaluation in qualitative research. However, a specific focus on its distinguishing feature of being “qualitative” while being implicitly acknowledged, was discussed only briefly (for example, Best 2004 ).

In 2014 a theme issue was published in this journal on “Methods, Materials, and Meanings: Designing Cultural Analysis,” discussing central issues in (cultural) qualitative research (Berezin 2014 ; Biernacki 2014 ; Glaeser 2014 ; Lamont and Swidler 2014 ; Spillman 2014). We agree with many of the arguments put forward, such as the risk of methodological tribalism, and that we should not waste energy on debating methods separated from research questions. Nonetheless, a clarification of the relation to what is called “quantitative research” is of outmost importance to avoid misunderstandings and misguided debates between “qualitative” and “quantitative” researchers. Our strategy means that researchers, “qualitative” or “quantitative” they may be, in their actual practice may combine qualitative work and quantitative work.

In this article we accomplish three tasks. First, we systematically survey the literature for meanings of qualitative research by looking at how researchers have defined it. Drawing upon existing knowledge we find that the different meanings and ideas of qualitative research are not yet coherently integrated into one satisfactory definition. Next, we advance our contribution by offering a definition of qualitative research and illustrate its meaning and use partially by expanding on the brief example introduced earlier related to Becker’s work ( 1963 ). We offer a systematic analysis of central themes of what researchers consider to be the core of “qualitative,” regardless of style of work. These themes – which we summarize in terms of four keywords: distinction, process, closeness, improved understanding – constitute part of our literature review, in which each one appears, sometimes with others, but never all in the same definition. They serve as the foundation of our contribution. Our categories are overlapping. Their use is primarily to organize the large amount of definitions we have identified and analyzed, and not necessarily to draw a clear distinction between them. Finally, we continue the elaboration discussed above on the advantages of a clear definition of qualitative research.

In a hermeneutic fashion we propose that there is something meaningful that deserves to be labelled “qualitative research” (Gadamer 1990 ). To approach the question “What is qualitative in qualitative research?” we have surveyed the literature. In conducting our survey we first traced the word’s etymology in dictionaries, encyclopedias, handbooks of the social sciences and of methods and textbooks, mainly in English, which is common to methodology courses. It should be noted that we have zoomed in on sociology and its literature. This discipline has been the site of the largest debate and development of methods that can be called “qualitative,” which suggests that this field should be examined in great detail.

In an ideal situation we should expect that one good definition, or at least some common ideas, would have emerged over the years. This common core of qualitative research should be so accepted that it would appear in at least some textbooks. Since this is not what we found, we decided to pursue an inductive approach to capture maximal variation in the field of qualitative research; we searched in a selection of handbooks, textbooks, book chapters, and books, to which we added the analysis of journal articles. Our sample comprises a total of 89 references.

In practice we focused on the discipline that has had a clear discussion of methods, namely sociology. We also conducted a broad search in the JSTOR database to identify scholarly sociology articles published between 1998 and 2017 in English with a focus on defining or explaining qualitative research. We specifically zoom in on this time frame because we would have expect that this more mature period would have produced clear discussions on the meaning of qualitative research. To find these articles we combined a number of keywords to search the content and/or the title: qualitative (which was always included), definition, empirical, research, methodology, studies, fieldwork, interview and observation .

As a second phase of our research we searched within nine major sociological journals ( American Journal of Sociology , Sociological Theory , American Sociological Review , Contemporary Sociology , Sociological Forum , Sociological Theory , Qualitative Research , Qualitative Sociology and Qualitative Sociology Review ) for articles also published during the past 19 years (1998–2017) that had the term “qualitative” in the title and attempted to define qualitative research.

Lastly we picked two additional journals, Qualitative Research and Qualitative Sociology , in which we could expect to find texts addressing the notion of “qualitative.” From Qualitative Research we chose Volume 14, Issue 6, December 2014, and from Qualitative Sociology we chose Volume 36, Issue 2, June 2017. Within each of these we selected the first article; then we picked the second article of three prior issues. Again we went back another three issues and investigated article number three. Finally we went back another three issues and perused article number four. This selection criteria was used to get a manageable sample for the analysis.

The coding process of the 89 references we gathered in our selected review began soon after the first round of material was gathered, and we reduced the complexity created by our maximum variation sampling (Snow and Anderson 1993 :22) to four different categories within which questions on the nature and properties of qualitative research were discussed. We call them: Qualitative and Quantitative Research, Qualitative Research, Fieldwork, and Grounded Theory. This – which may appear as an illogical grouping – merely reflects the “context” in which the matter of “qualitative” is discussed. If the selection process of the material – books and articles – was informed by pre-knowledge, we used an inductive strategy to code the material. When studying our material, we identified four central notions related to “qualitative” that appear in various combinations in the literature which indicate what is the core of qualitative research. We have labeled them: “distinctions”, “process,” “closeness,” and “improved understanding.” During the research process the categories and notions were improved, refined, changed, and reordered. The coding ended when a sense of saturation in the material arose. In the presentation below all quotations and references come from our empirical material of texts on qualitative research.

Analysis – What is Qualitative Research?

In this section we describe the four categories we identified in the coding, how they differently discuss qualitative research, as well as their overall content. Some salient quotations are selected to represent the type of text sorted under each of the four categories. What we present are examples from the literature.

Qualitative and Quantitative

This analytic category comprises quotations comparing qualitative and quantitative research, a distinction that is frequently used (Brown 2010 :231); in effect this is a conceptual pair that structures the discussion and that may be associated with opposing interests. While the general goal of quantitative and qualitative research is the same – to understand the world better – their methodologies and focus in certain respects differ substantially (Becker 1966 :55). Quantity refers to that property of something that can be determined by measurement. In a dictionary of Statistics and Methodology we find that “(a) When referring to *variables, ‘qualitative’ is another term for *categorical or *nominal. (b) When speaking of kinds of research, ‘qualitative’ refers to studies of subjects that are hard to quantify, such as art history. Qualitative research tends to be a residual category for almost any kind of non-quantitative research” (Stiles 1998:183). But it should be obvious that one could employ a quantitative approach when studying, for example, art history.

The same dictionary states that quantitative is “said of variables or research that can be handled numerically, usually (too sharply) contrasted with *qualitative variables and research” (Stiles 1998:184). From a qualitative perspective “quantitative research” is about numbers and counting, and from a quantitative perspective qualitative research is everything that is not about numbers. But this does not say much about what is “qualitative.” If we turn to encyclopedias we find that in the 1932 edition of the Encyclopedia of the Social Sciences there is no mention of “qualitative.” In the Encyclopedia from 1968 we can read:

Qualitative Analysis. For methods of obtaining, analyzing, and describing data, see [the various entries:] CONTENT ANALYSIS; COUNTED DATA; EVALUATION RESEARCH, FIELD WORK; GRAPHIC PRESENTATION; HISTORIOGRAPHY, especially the article on THE RHETORIC OF HISTORY; INTERVIEWING; OBSERVATION; PERSONALITY MEASUREMENT; PROJECTIVE METHODS; PSYCHOANALYSIS, article on EXPERIMENTAL METHODS; SURVEY ANALYSIS, TABULAR PRESENTATION; TYPOLOGIES. (Vol. 13:225)

Some, like Alford, divide researchers into methodologists or, in his words, “quantitative and qualitative specialists” (Alford 1998 :12). Qualitative research uses a variety of methods, such as intensive interviews or in-depth analysis of historical materials, and it is concerned with a comprehensive account of some event or unit (King et al. 1994 :4). Like quantitative research it can be utilized to study a variety of issues, but it tends to focus on meanings and motivations that underlie cultural symbols, personal experiences, phenomena and detailed understanding of processes in the social world. In short, qualitative research centers on understanding processes, experiences, and the meanings people assign to things (Kalof et al. 2008 :79).

Others simply say that qualitative methods are inherently unscientific (Jovanović 2011 :19). Hood, for instance, argues that words are intrinsically less precise than numbers, and that they are therefore more prone to subjective analysis, leading to biased results (Hood 2006 :219). Qualitative methodologies have raised concerns over the limitations of quantitative templates (Brady et al. 2004 :4). Scholars such as King et al. ( 1994 ), for instance, argue that non-statistical research can produce more reliable results if researchers pay attention to the rules of scientific inference commonly stated in quantitative research. Also, researchers such as Becker ( 1966 :59; 1970 :42–43) have asserted that, if conducted properly, qualitative research and in particular ethnographic field methods, can lead to more accurate results than quantitative studies, in particular, survey research and laboratory experiments.

Some researchers, such as Kalof, Dan, and Dietz ( 2008 :79) claim that the boundaries between the two approaches are becoming blurred, and Small ( 2009 ) argues that currently much qualitative research (especially in North America) tries unsuccessfully and unnecessarily to emulate quantitative standards. For others, qualitative research tends to be more humanistic and discursive (King et al. 1994 :4). Ragin ( 1994 ), and similarly also Becker, ( 1996 :53), Marchel and Owens ( 2007 :303) think that the main distinction between the two styles is overstated and does not rest on the simple dichotomy of “numbers versus words” (Ragin 1994 :xii). Some claim that quantitative data can be utilized to discover associations, but in order to unveil cause and effect a complex research design involving the use of qualitative approaches needs to be devised (Gilbert 2009 :35). Consequently, qualitative data are useful for understanding the nuances lying beyond those processes as they unfold (Gilbert 2009 :35). Others contend that qualitative research is particularly well suited both to identify causality and to uncover fine descriptive distinctions (Fine and Hallett 2014 ; Lichterman and Isaac Reed 2014 ; Katz 2015 ).

There are other ways to separate these two traditions, including normative statements about what qualitative research should be (that is, better or worse than quantitative approaches, concerned with scientific approaches to societal change or vice versa; Snow and Morrill 1995 ; Denzin and Lincoln 2005 ), or whether it should develop falsifiable statements; Best 2004 ).

We propose that quantitative research is largely concerned with pre-determined variables (Small 2008 ); the analysis concerns the relations between variables. These categories are primarily not questioned in the study, only their frequency or degree, or the correlations between them (cf. Franzosi 2016 ). If a researcher studies wage differences between women and men, he or she works with given categories: x number of men are compared with y number of women, with a certain wage attributed to each person. The idea is not to move beyond the given categories of wage, men and women; they are the starting point as well as the end point, and undergo no “qualitative change.” Qualitative research, in contrast, investigates relations between categories that are themselves subject to change in the research process. Returning to Becker’s study ( 1963 ), we see that he questioned pre-dispositional theories of deviant behavior working with pre-determined variables such as an individual’s combination of personal qualities or emotional problems. His take, in contrast, was to understand marijuana consumption by developing “variables” as part of the investigation. Thereby he presented new variables, or as we would say today, theoretical concepts, but which are grounded in the empirical material.

Qualitative Research

This category contains quotations that refer to descriptions of qualitative research without making comparisons with quantitative research. Researchers such as Denzin and Lincoln, who have written a series of influential handbooks on qualitative methods (1994; Denzin and Lincoln 2003 ; 2005 ), citing Nelson et al. (1992:4), argue that because qualitative research is “interdisciplinary, transdisciplinary, and sometimes counterdisciplinary” it is difficult to derive one single definition of it (Jovanović 2011 :3). According to them, in fact, “the field” is “many things at the same time,” involving contradictions, tensions over its focus, methods, and how to derive interpretations and findings ( 2003 : 11). Similarly, others, such as Flick ( 2007 :ix–x) contend that agreeing on an accepted definition has increasingly become problematic, and that qualitative research has possibly matured different identities. However, Best holds that “the proliferation of many sorts of activities under the label of qualitative sociology threatens to confuse our discussions” ( 2004 :54). Atkinson’s position is more definite: “the current state of qualitative research and research methods is confused” ( 2005 :3–4).

Qualitative research is about interpretation (Blumer 1969 ; Strauss and Corbin 1998 ; Denzin and Lincoln 2003 ), or Verstehen [understanding] (Frankfort-Nachmias and Nachmias 1996 ). It is “multi-method,” involving the collection and use of a variety of empirical materials (Denzin and Lincoln 1998; Silverman 2013 ) and approaches (Silverman 2005 ; Flick 2007 ). It focuses not only on the objective nature of behavior but also on its subjective meanings: individuals’ own accounts of their attitudes, motivations, behavior (McIntyre 2005 :127; Creswell 2009 ), events and situations (Bryman 1989) – what people say and do in specific places and institutions (Goodwin and Horowitz 2002 :35–36) in social and temporal contexts (Morrill and Fine 1997). For this reason, following Weber ([1921-22] 1978), it can be described as an interpretative science (McIntyre 2005 :127). But could quantitative research also be concerned with these questions? Also, as pointed out below, does all qualitative research focus on subjective meaning, as some scholars suggest?

Others also distinguish qualitative research by claiming that it collects data using a naturalistic approach (Denzin and Lincoln 2005 :2; Creswell 2009 ), focusing on the meaning actors ascribe to their actions. But again, does all qualitative research need to be collected in situ? And does qualitative research have to be inherently concerned with meaning? Flick ( 2007 ), referring to Denzin and Lincoln ( 2005 ), mentions conversation analysis as an example of qualitative research that is not concerned with the meanings people bring to a situation, but rather with the formal organization of talk. Still others, such as Ragin ( 1994 :85), note that qualitative research is often (especially early on in the project, we would add) less structured than other kinds of social research – a characteristic connected to its flexibility and that can lead both to potentially better, but also worse results. But is this not a feature of this type of research, rather than a defining description of its essence? Wouldn’t this comment also apply, albeit to varying degrees, to quantitative research?

In addition, Strauss ( 2003 ), along with others, such as Alvesson and Kärreman ( 2011 :10–76), argue that qualitative researchers struggle to capture and represent complex phenomena partially because they tend to collect a large amount of data. While his analysis is correct at some points – “It is necessary to do detailed, intensive, microscopic examination of the data in order to bring out the amazing complexity of what lies in, behind, and beyond those data” (Strauss 2003 :10) – much of his analysis concerns the supposed focus of qualitative research and its challenges, rather than exactly what it is about. But even in this instance we would make a weak case arguing that these are strictly the defining features of qualitative research. Some researchers seem to focus on the approach or the methods used, or even on the way material is analyzed. Several researchers stress the naturalistic assumption of investigating the world, suggesting that meaning and interpretation appear to be a core matter of qualitative research.

We can also see that in this category there is no consensus about specific qualitative methods nor about qualitative data. Many emphasize interpretation, but quantitative research, too, involves interpretation; the results of a regression analysis, for example, certainly have to be interpreted, and the form of meta-analysis that factor analysis provides indeed requires interpretation However, there is no interpretation of quantitative raw data, i.e., numbers in tables. One common thread is that qualitative researchers have to get to grips with their data in order to understand what is being studied in great detail, irrespective of the type of empirical material that is being analyzed. This observation is connected to the fact that qualitative researchers routinely make several adjustments of focus and research design as their studies progress, in many cases until the very end of the project (Kalof et al. 2008 ). If you, like Becker, do not start out with a detailed theory, adjustments such as the emergence and refinement of research questions will occur during the research process. We have thus found a number of useful reflections about qualitative research scattered across different sources, but none of them effectively describe the defining characteristics of this approach.

Although qualitative research does not appear to be defined in terms of a specific method, it is certainly common that fieldwork, i.e., research that entails that the researcher spends considerable time in the field that is studied and use the knowledge gained as data, is seen as emblematic of or even identical to qualitative research. But because we understand that fieldwork tends to focus primarily on the collection and analysis of qualitative data, we expected to find within it discussions on the meaning of “qualitative.” But, again, this was not the case.

Instead, we found material on the history of this approach (for example, Frankfort-Nachmias and Nachmias 1996 ; Atkinson et al. 2001), including how it has changed; for example, by adopting a more self-reflexive practice (Heyl 2001), as well as the different nomenclature that has been adopted, such as fieldwork, ethnography, qualitative research, naturalistic research, participant observation and so on (for example, Lofland et al. 2006 ; Gans 1999 ).

We retrieved definitions of ethnography, such as “the study of people acting in the natural courses of their daily lives,” involving a “resocialization of the researcher” (Emerson 1988 :1) through intense immersion in others’ social worlds (see also examples in Hammersley 2018 ). This may be accomplished by direct observation and also participation (Neuman 2007 :276), although others, such as Denzin ( 1970 :185), have long recognized other types of observation, including non-participant (“fly on the wall”). In this category we have also isolated claims and opposing views, arguing that this type of research is distinguished primarily by where it is conducted (natural settings) (Hughes 1971:496), and how it is carried out (a variety of methods are applied) or, for some most importantly, by involving an active, empathetic immersion in those being studied (Emerson 1988 :2). We also retrieved descriptions of the goals it attends in relation to how it is taught (understanding subjective meanings of the people studied, primarily develop theory, or contribute to social change) (see for example, Corte and Irwin 2017 ; Frankfort-Nachmias and Nachmias 1996 :281; Trier-Bieniek 2012 :639) by collecting the richest possible data (Lofland et al. 2006 ) to derive “thick descriptions” (Geertz 1973 ), and/or to aim at theoretical statements of general scope and applicability (for example, Emerson 1988 ; Fine 2003 ). We have identified guidelines on how to evaluate it (for example Becker 1996 ; Lamont 2004 ) and have retrieved instructions on how it should be conducted (for example, Lofland et al. 2006 ). For instance, analysis should take place while the data gathering unfolds (Emerson 1988 ; Hammersley and Atkinson 2007 ; Lofland et al. 2006 ), observations should be of long duration (Becker 1970 :54; Goffman 1989 ), and data should be of high quantity (Becker 1970 :52–53), as well as other questionable distinctions between fieldwork and other methods:

Field studies differ from other methods of research in that the researcher performs the task of selecting topics, decides what questions to ask, and forges interest in the course of the research itself . This is in sharp contrast to many ‘theory-driven’ and ‘hypothesis-testing’ methods. (Lofland and Lofland 1995 :5)

But could not, for example, a strictly interview-based study be carried out with the same amount of flexibility, such as sequential interviewing (for example, Small 2009 )? Once again, are quantitative approaches really as inflexible as some qualitative researchers think? Moreover, this category stresses the role of the actors’ meaning, which requires knowledge and close interaction with people, their practices and their lifeworld.

It is clear that field studies – which are seen by some as the “gold standard” of qualitative research – are nonetheless only one way of doing qualitative research. There are other methods, but it is not clear why some are more qualitative than others, or why they are better or worse. Fieldwork is characterized by interaction with the field (the material) and understanding of the phenomenon that is being studied. In Becker’s case, he had general experience from fields in which marihuana was used, based on which he did interviews with actual users in several fields.

Grounded Theory

Another major category we identified in our sample is Grounded Theory. We found descriptions of it most clearly in Glaser and Strauss’ ([1967] 2010 ) original articulation, Strauss and Corbin ( 1998 ) and Charmaz ( 2006 ), as well as many other accounts of what it is for: generating and testing theory (Strauss 2003 :xi). We identified explanations of how this task can be accomplished – such as through two main procedures: constant comparison and theoretical sampling (Emerson 1998:96), and how using it has helped researchers to “think differently” (for example, Strauss and Corbin 1998 :1). We also read descriptions of its main traits, what it entails and fosters – for instance, an exceptional flexibility, an inductive approach (Strauss and Corbin 1998 :31–33; 1990; Esterberg 2002 :7), an ability to step back and critically analyze situations, recognize tendencies towards bias, think abstractly and be open to criticism, enhance sensitivity towards the words and actions of respondents, and develop a sense of absorption and devotion to the research process (Strauss and Corbin 1998 :5–6). Accordingly, we identified discussions of the value of triangulating different methods (both using and not using grounded theory), including quantitative ones, and theories to achieve theoretical development (most comprehensively in Denzin 1970 ; Strauss and Corbin 1998 ; Timmermans and Tavory 2012 ). We have also located arguments about how its practice helps to systematize data collection, analysis and presentation of results (Glaser and Strauss [1967] 2010 :16).

Grounded theory offers a systematic approach which requires researchers to get close to the field; closeness is a requirement of identifying questions and developing new concepts or making further distinctions with regard to old concepts. In contrast to other qualitative approaches, grounded theory emphasizes the detailed coding process, and the numerous fine-tuned distinctions that the researcher makes during the process. Within this category, too, we could not find a satisfying discussion of the meaning of qualitative research.

Defining Qualitative Research

In sum, our analysis shows that some notions reappear in the discussion of qualitative research, such as understanding, interpretation, “getting close” and making distinctions. These notions capture aspects of what we think is “qualitative.” However, a comprehensive definition that is useful and that can further develop the field is lacking, and not even a clear picture of its essential elements appears. In other words no definition emerges from our data, and in our research process we have moved back and forth between our empirical data and the attempt to present a definition. Our concrete strategy, as stated above, is to relate qualitative and quantitative research, or more specifically, qualitative and quantitative work. We use an ideal-typical notion of quantitative research which relies on taken for granted and numbered variables. This means that the data consists of variables on different scales, such as ordinal, but frequently ratio and absolute scales, and the representation of the numbers to the variables, i.e. the justification of the assignment of numbers to object or phenomenon, are not questioned, though the validity may be questioned. In this section we return to the notion of quality and try to clarify it while presenting our contribution.

Broadly, research refers to the activity performed by people trained to obtain knowledge through systematic procedures. Notions such as “objectivity” and “reflexivity,” “systematic,” “theory,” “evidence” and “openness” are here taken for granted in any type of research. Next, building on our empirical analysis we explain the four notions that we have identified as central to qualitative work: distinctions, process, closeness, and improved understanding. In discussing them, ultimately in relation to one another, we make their meaning even more precise. Our idea, in short, is that only when these ideas that we present separately for analytic purposes are brought together can we speak of qualitative research.

Distinctions

We believe that the possibility of making new distinctions is one the defining characteristics of qualitative research. It clearly sets it apart from quantitative analysis which works with taken-for-granted variables, albeit as mentioned, meta-analyses, for example, factor analysis may result in new variables. “Quality” refers essentially to distinctions, as already pointed out by Aristotle. He discusses the term “qualitative” commenting: “By a quality I mean that in virtue of which things are said to be qualified somehow” (Aristotle 1984:14). Quality is about what something is or has, which means that the distinction from its environment is crucial. We see qualitative research as a process in which significant new distinctions are made to the scholarly community; to make distinctions is a key aspect of obtaining new knowledge; a point, as we will see, that also has implications for “quantitative research.” The notion of being “significant” is paramount. New distinctions by themselves are not enough; just adding concepts only increases complexity without furthering our knowledge. The significance of new distinctions is judged against the communal knowledge of the research community. To enable this discussion and judgements central elements of rational discussion are required (cf. Habermas [1981] 1987 ; Davidsson [ 1988 ] 2001) to identify what is new and relevant scientific knowledge. Relatedly, Ragin alludes to the idea of new and useful knowledge at a more concrete level: “Qualitative methods are appropriate for in-depth examination of cases because they aid the identification of key features of cases. Most qualitative methods enhance data” (1994:79). When Becker ( 1963 ) studied deviant behavior and investigated how people became marihuana smokers, he made distinctions between the ways in which people learned how to smoke. This is a classic example of how the strategy of “getting close” to the material, for example the text, people or pictures that are subject to analysis, may enable researchers to obtain deeper insight and new knowledge by making distinctions – in this instance on the initial notion of learning how to smoke. Others have stressed the making of distinctions in relation to coding or theorizing. Emerson et al. ( 1995 ), for example, hold that “qualitative coding is a way of opening up avenues of inquiry,” meaning that the researcher identifies and develops concepts and analytic insights through close examination of and reflection on data (Emerson et al. 1995 :151). Goodwin and Horowitz highlight making distinctions in relation to theory-building writing: “Close engagement with their cases typically requires qualitative researchers to adapt existing theories or to make new conceptual distinctions or theoretical arguments to accommodate new data” ( 2002 : 37). In the ideal-typical quantitative research only existing and so to speak, given, variables would be used. If this is the case no new distinction are made. But, would not also many “quantitative” researchers make new distinctions?

Process does not merely suggest that research takes time. It mainly implies that qualitative new knowledge results from a process that involves several phases, and above all iteration. Qualitative research is about oscillation between theory and evidence, analysis and generating material, between first- and second -order constructs (Schütz 1962 :59), between getting in contact with something, finding sources, becoming deeply familiar with a topic, and then distilling and communicating some of its essential features. The main point is that the categories that the researcher uses, and perhaps takes for granted at the beginning of the research process, usually undergo qualitative changes resulting from what is found. Becker describes how he tested hypotheses and let the jargon of the users develop into theoretical concepts. This happens over time while the study is being conducted, exemplifying what we mean by process.

In the research process, a pilot-study may be used to get a first glance of, for example, the field, how to approach it, and what methods can be used, after which the method and theory are chosen or refined before the main study begins. Thus, the empirical material is often central from the start of the project and frequently leads to adjustments by the researcher. Likewise, during the main study categories are not fixed; the empirical material is seen in light of the theory used, but it is also given the opportunity to kick back, thereby resisting attempts to apply theoretical straightjackets (Becker 1970 :43). In this process, coding and analysis are interwoven, and thus are often important steps for getting closer to the phenomenon and deciding what to focus on next. Becker began his research by interviewing musicians close to him, then asking them to refer him to other musicians, and later on doubling his original sample of about 25 to include individuals in other professions (Becker 1973:46). Additionally, he made use of some participant observation, documents, and interviews with opiate users made available to him by colleagues. As his inductive theory of deviance evolved, Becker expanded his sample in order to fine tune it, and test the accuracy and generality of his hypotheses. In addition, he introduced a negative case and discussed the null hypothesis ( 1963 :44). His phasic career model is thus based on a research design that embraces processual work. Typically, process means to move between “theory” and “material” but also to deal with negative cases, and Becker ( 1998 ) describes how discovering these negative cases impacted his research design and ultimately its findings.

Obviously, all research is process-oriented to some degree. The point is that the ideal-typical quantitative process does not imply change of the data, and iteration between data, evidence, hypotheses, empirical work, and theory. The data, quantified variables, are, in most cases fixed. Merging of data, which of course can be done in a quantitative research process, does not mean new data. New hypotheses are frequently tested, but the “raw data is often the “the same.” Obviously, over time new datasets are made available and put into use.

Another characteristic that is emphasized in our sample is that qualitative researchers – and in particular ethnographers – can, or as Goffman put it, ought to ( 1989 ), get closer to the phenomenon being studied and their data than quantitative researchers (for example, Silverman 2009 :85). Put differently, essentially because of their methods qualitative researchers get into direct close contact with those being investigated and/or the material, such as texts, being analyzed. Becker started out his interview study, as we noted, by talking to those he knew in the field of music to get closer to the phenomenon he was studying. By conducting interviews he got even closer. Had he done more observations, he would undoubtedly have got even closer to the field.

Additionally, ethnographers’ design enables researchers to follow the field over time, and the research they do is almost by definition longitudinal, though the time in the field is studied obviously differs between studies. The general characteristic of closeness over time maximizes the chances of unexpected events, new data (related, for example, to archival research as additional sources, and for ethnography for situations not necessarily previously thought of as instrumental – what Mannay and Morgan ( 2015 ) term the “waiting field”), serendipity (Merton and Barber 2004 ; Åkerström 2013 ), and possibly reactivity, as well as the opportunity to observe disrupted patterns that translate into exemplars of negative cases. Two classic examples of this are Becker’s finding of what medical students call “crocks” (Becker et al. 1961 :317), and Geertz’s ( 1973 ) study of “deep play” in Balinese society.

By getting and staying so close to their data – be it pictures, text or humans interacting (Becker was himself a musician) – for a long time, as the research progressively focuses, qualitative researchers are prompted to continually test their hunches, presuppositions and hypotheses. They test them against a reality that often (but certainly not always), and practically, as well as metaphorically, talks back, whether by validating them, or disqualifying their premises – correctly, as well as incorrectly (Fine 2003 ; Becker 1970 ). This testing nonetheless often leads to new directions for the research. Becker, for example, says that he was initially reading psychological theories, but when facing the data he develops a theory that looks at, you may say, everything but psychological dispositions to explain the use of marihuana. Especially researchers involved with ethnographic methods have a fairly unique opportunity to dig up and then test (in a circular, continuous and temporal way) new research questions and findings as the research progresses, and thereby to derive previously unimagined and uncharted distinctions by getting closer to the phenomenon under study.

Let us stress that getting close is by no means restricted to ethnography. The notion of hermeneutic circle and hermeneutics as a general way of understanding implies that we must get close to the details in order to get the big picture. This also means that qualitative researchers can literally also make use of details of pictures as evidence (cf. Harper 2002). Thus, researchers may get closer both when generating the material or when analyzing it.

Quantitative research, we maintain, in the ideal-typical representation cannot get closer to the data. The data is essentially numbers in tables making up the variables (Franzosi 2016 :138). The data may originally have been “qualitative,” but once reduced to numbers there can only be a type of “hermeneutics” about what the number may stand for. The numbers themselves, however, are non-ambiguous. Thus, in quantitative research, interpretation, if done, is not about the data itself—the numbers—but what the numbers stand for. It follows that the interpretation is essentially done in a more “speculative” mode without direct empirical evidence (cf. Becker 2017 ).

Improved Understanding

While distinction, process and getting closer refer to the qualitative work of the researcher, improved understanding refers to its conditions and outcome of this work. Understanding cuts deeper than explanation, which to some may mean a causally verified correlation between variables. The notion of explanation presupposes the notion of understanding since explanation does not include an idea of how knowledge is gained (Manicas 2006 : 15). Understanding, we argue, is the core concept of what we call the outcome of the process when research has made use of all the other elements that were integrated in the research. Understanding, then, has a special status in qualitative research since it refers both to the conditions of knowledge and the outcome of the process. Understanding can to some extent be seen as the condition of explanation and occurs in a process of interpretation, which naturally refers to meaning (Gadamer 1990 ). It is fundamentally connected to knowing, and to the knowing of how to do things (Heidegger [1927] 2001 ). Conceptually the term hermeneutics is used to account for this process. Heidegger ties hermeneutics to human being and not possible to separate from the understanding of being ( 1988 ). Here we use it in a broader sense, and more connected to method in general (cf. Seiffert 1992 ). The abovementioned aspects – for example, “objectivity” and “reflexivity” – of the approach are conditions of scientific understanding. Understanding is the result of a circular process and means that the parts are understood in light of the whole, and vice versa. Understanding presupposes pre-understanding, or in other words, some knowledge of the phenomenon studied. The pre-understanding, even in the form of prejudices, are in qualitative research process, which we see as iterative, questioned, which gradually or suddenly change due to the iteration of data, evidence and concepts. However, qualitative research generates understanding in the iterative process when the researcher gets closer to the data, e.g., by going back and forth between field and analysis in a process that generates new data that changes the evidence, and, ultimately, the findings. Questioning, to ask questions, and put what one assumes—prejudices and presumption—in question, is central to understand something (Heidegger [1927] 2001 ; Gadamer 1990 :368–384). We propose that this iterative process in which the process of understanding occurs is characteristic of qualitative research.

Improved understanding means that we obtain scientific knowledge of something that we as a scholarly community did not know before, or that we get to know something better. It means that we understand more about how parts are related to one another, and to other things we already understand (see also Fine and Hallett 2014 ). Understanding is an important condition for qualitative research. It is not enough to identify correlations, make distinctions, and work in a process in which one gets close to the field or phenomena. Understanding is accomplished when the elements are integrated in an iterative process.

It is, moreover, possible to understand many things, and researchers, just like children, may come to understand new things every day as they engage with the world. This subjective condition of understanding – namely, that a person gains a better understanding of something –is easily met. To be qualified as “scientific,” the understanding must be general and useful to many; it must be public. But even this generally accessible understanding is not enough in order to speak of “scientific understanding.” Though we as a collective can increase understanding of everything in virtually all potential directions as a result also of qualitative work, we refrain from this “objective” way of understanding, which has no means of discriminating between what we gain in understanding. Scientific understanding means that it is deemed relevant from the scientific horizon (compare Schütz 1962 : 35–38, 46, 63), and that it rests on the pre-understanding that the scientists have and must have in order to understand. In other words, the understanding gained must be deemed useful by other researchers, so that they can build on it. We thus see understanding from a pragmatic, rather than a subjective or objective perspective. Improved understanding is related to the question(s) at hand. Understanding, in order to represent an improvement, must be an improvement in relation to the existing body of knowledge of the scientific community (James [ 1907 ] 1955). Scientific understanding is, by definition, collective, as expressed in Weber’s famous note on objectivity, namely that scientific work aims at truths “which … can claim, even for a Chinese, the validity appropriate to an empirical analysis” ([1904] 1949 :59). By qualifying “improved understanding” we argue that it is a general defining characteristic of qualitative research. Becker‘s ( 1966 ) study and other research of deviant behavior increased our understanding of the social learning processes of how individuals start a behavior. And it also added new knowledge about the labeling of deviant behavior as a social process. Few studies, of course, make the same large contribution as Becker’s, but are nonetheless qualitative research.

Understanding in the phenomenological sense, which is a hallmark of qualitative research, we argue, requires meaning and this meaning is derived from the context, and above all the data being analyzed. The ideal-typical quantitative research operates with given variables with different numbers. This type of material is not enough to establish meaning at the level that truly justifies understanding. In other words, many social science explanations offer ideas about correlations or even causal relations, but this does not mean that the meaning at the level of the data analyzed, is understood. This leads us to say that there are indeed many explanations that meet the criteria of understanding, for example the explanation of how one becomes a marihuana smoker presented by Becker. However, we may also understand a phenomenon without explaining it, and we may have potential explanations, or better correlations, that are not really understood.

We may speak more generally of quantitative research and its data to clarify what we see as an important distinction. The “raw data” that quantitative research—as an idealtypical activity, refers to is not available for further analysis; the numbers, once created, are not to be questioned (Franzosi 2016 : 138). If the researcher is to do “more” or “change” something, this will be done by conjectures based on theoretical knowledge or based on the researcher’s lifeworld. Both qualitative and quantitative research is based on the lifeworld, and all researchers use prejudices and pre-understanding in the research process. This idea is present in the works of Heidegger ( 2001 ) and Heisenberg (cited in Franzosi 2010 :619). Qualitative research, as we argued, involves the interaction and questioning of concepts (theory), data, and evidence.

Ragin ( 2004 :22) points out that “a good definition of qualitative research should be inclusive and should emphasize its key strengths and features, not what it lacks (for example, the use of sophisticated quantitative techniques).” We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. Qualitative research, as defined here, is consequently a combination of two criteria: (i) how to do things –namely, generating and analyzing empirical material, in an iterative process in which one gets closer by making distinctions, and (ii) the outcome –improved understanding novel to the scholarly community. Is our definition applicable to our own study? In this study we have closely read the empirical material that we generated, and the novel distinction of the notion “qualitative research” is the outcome of an iterative process in which both deduction and induction were involved, in which we identified the categories that we analyzed. We thus claim to meet the first criteria, “how to do things.” The second criteria cannot be judged but in a partial way by us, namely that the “outcome” —in concrete form the definition-improves our understanding to others in the scientific community.

We have defined qualitative research, or qualitative scientific work, in relation to quantitative scientific work. Given this definition, qualitative research is about questioning the pre-given (taken for granted) variables, but it is thus also about making new distinctions of any type of phenomenon, for example, by coining new concepts, including the identification of new variables. This process, as we have discussed, is carried out in relation to empirical material, previous research, and thus in relation to theory. Theory and previous research cannot be escaped or bracketed. According to hermeneutic principles all scientific work is grounded in the lifeworld, and as social scientists we can thus never fully bracket our pre-understanding.

We have proposed that quantitative research, as an idealtype, is concerned with pre-determined variables (Small 2008 ). Variables are epistemically fixed, but can vary in terms of dimensions, such as frequency or number. Age is an example; as a variable it can take on different numbers. In relation to quantitative research, qualitative research does not reduce its material to number and variables. If this is done the process of comes to a halt, the researcher gets more distanced from her data, and it makes it no longer possible to make new distinctions that increase our understanding. We have above discussed the components of our definition in relation to quantitative research. Our conclusion is that in the research that is called quantitative there are frequent and necessary qualitative elements.

Further, comparative empirical research on researchers primarily working with ”quantitative” approaches and those working with ”qualitative” approaches, we propose, would perhaps show that there are many similarities in practices of these two approaches. This is not to deny dissimilarities, or the different epistemic and ontic presuppositions that may be more or less strongly associated with the two different strands (see Goertz and Mahoney 2012 ). Our point is nonetheless that prejudices and preconceptions about researchers are unproductive, and that as other researchers have argued, differences may be exaggerated (e.g., Becker 1996 : 53, 2017 ; Marchel and Owens 2007 :303; Ragin 1994 ), and that a qualitative dimension is present in both kinds of work.

Several things follow from our findings. The most important result is the relation to quantitative research. In our analysis we have separated qualitative research from quantitative research. The point is not to label individual researchers, methods, projects, or works as either “quantitative” or “qualitative.” By analyzing, i.e., taking apart, the notions of quantitative and qualitative, we hope to have shown the elements of qualitative research. Our definition captures the elements, and how they, when combined in practice, generate understanding. As many of the quotations we have used suggest, one conclusion of our study holds that qualitative approaches are not inherently connected with a specific method. Put differently, none of the methods that are frequently labelled “qualitative,” such as interviews or participant observation, are inherently “qualitative.” What matters, given our definition, is whether one works qualitatively or quantitatively in the research process, until the results are produced. Consequently, our analysis also suggests that those researchers working with what in the literature and in jargon is often called “quantitative research” are almost bound to make use of what we have identified as qualitative elements in any research project. Our findings also suggest that many” quantitative” researchers, at least to some extent, are engaged with qualitative work, such as when research questions are developed, variables are constructed and combined, and hypotheses are formulated. Furthermore, a research project may hover between “qualitative” and “quantitative” or start out as “qualitative” and later move into a “quantitative” (a distinct strategy that is not similar to “mixed methods” or just simply combining induction and deduction). More generally speaking, the categories of “qualitative” and “quantitative,” unfortunately, often cover up practices, and it may lead to “camps” of researchers opposing one another. For example, regardless of the researcher is primarily oriented to “quantitative” or “qualitative” research, the role of theory is neglected (cf. Swedberg 2017 ). Our results open up for an interaction not characterized by differences, but by different emphasis, and similarities.

Let us take two examples to briefly indicate how qualitative elements can fruitfully be combined with quantitative. Franzosi ( 2010 ) has discussed the relations between quantitative and qualitative approaches, and more specifically the relation between words and numbers. He analyzes texts and argues that scientific meaning cannot be reduced to numbers. Put differently, the meaning of the numbers is to be understood by what is taken for granted, and what is part of the lifeworld (Schütz 1962 ). Franzosi shows how one can go about using qualitative and quantitative methods and data to address scientific questions analyzing violence in Italy at the time when fascism was rising (1919–1922). Aspers ( 2006 ) studied the meaning of fashion photographers. He uses an empirical phenomenological approach, and establishes meaning at the level of actors. In a second step this meaning, and the different ideal-typical photographers constructed as a result of participant observation and interviews, are tested using quantitative data from a database; in the first phase to verify the different ideal-types, in the second phase to use these types to establish new knowledge about the types. In both of these cases—and more examples can be found—authors move from qualitative data and try to keep the meaning established when using the quantitative data.

A second main result of our study is that a definition, and we provided one, offers a way for research to clarify, and even evaluate, what is done. Hence, our definition can guide researchers and students, informing them on how to think about concrete research problems they face, and to show what it means to get closer in a process in which new distinctions are made. The definition can also be used to evaluate the results, given that it is a standard of evaluation (cf. Hammersley 2007 ), to see whether new distinctions are made and whether this improves our understanding of what is researched, in addition to the evaluation of how the research was conducted. By making what is qualitative research explicit it becomes easier to communicate findings, and it is thereby much harder to fly under the radar with substandard research since there are standards of evaluation which make it easier to separate “good” from “not so good” qualitative research.

To conclude, our analysis, which ends with a definition of qualitative research can thus both address the “internal” issues of what is qualitative research, and the “external” critiques that make it harder to do qualitative research, to which both pressure from quantitative methods and general changes in society contribute.

Acknowledgements

Financial Support for this research is given by the European Research Council, CEV (263699). The authors are grateful to Susann Krieglsteiner for assistance in collecting the data. The paper has benefitted from the many useful comments by the three reviewers and the editor, comments by members of the Uppsala Laboratory of Economic Sociology, as well as Jukka Gronow, Sebastian Kohl, Marcin Serafin, Richard Swedberg, Anders Vassenden and Turid Rødne.

Biographies

is professor of sociology at the Department of Sociology, Uppsala University and Universität St. Gallen. His main focus is economic sociology, and in particular, markets. He has published numerous articles and books, including Orderly Fashion (Princeton University Press 2010), Markets (Polity Press 2011) and Re-Imagining Economic Sociology (edited with N. Dodd, Oxford University Press 2015). His book Ethnographic Methods (in Swedish) has already gone through several editions.

is associate professor of sociology at the Department of Media and Social Sciences, University of Stavanger. His research has been published in journals such as Social Psychology Quarterly, Sociological Theory, Teaching Sociology, and Music and Arts in Action. As an ethnographer he is working on a book on he social world of big-wave surfing.

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Contributor Information

Patrik Aspers, Email: [email protected] .

Ugo Corte, Email: [email protected] .

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Qualitative research method-interviewing and observation
Interviewing. This is the most common format of data collection in qualitative research. According to Oakley, qualitative interview is a type of framework in which the practices and standards be not only recorded, but also achieved, challenged and as well as reinforced.[] As no research interview lacks structure[] most of the qualitative research interviews are either semi-structured, lightly ...
Types of Interviews in Research
An interview is a qualitative research method that relies on asking questions in order to collect data. Interviews involve two or more people, one of whom is the interviewer asking the questions. ... The questions and the order in which they are asked are not set. Instead, the interview can proceed more spontaneously, based on the participant ...
PDF TIPSHEET QUALITATIVE INTERVIEWING
result, the structure of interviews can range from loose conversations to structured exchanges in which all interviewees are asked the exact same set of questions. Your choice of interview structure should reflect the goals and stage of your research. Less structured interviews are most appropriate for early stages of research because they
How to Conduct a Qualitative Interview (2024 Guide)
Here are some steps on how to analyze a qualitative interview: 1. Transcription. The first step is transcribing the interview into text format to have a written record of the conversation. This step is essential to ensure that you can refer back to the interview data and identify the important aspects of the interview.
Interviews in the social sciences
In-depth interviews are a versatile form of qualitative data collection used by researchers across the social sciences. In this Primer, Knott et al. describe the stages and challenges involved in ...
PDF Interviewing in Qualitative Research
Interviewing in qualitative research is much like good conversation. It is the process of extracting people's experiences, describing how they felt about them and how they affected their lives. ... Use a quiet and private setting for interviews; Use good interview techniques. After the interview, the interviewer notes the following:
Qualitative Interviewing
Interviewing is often described as the "foundational" method of qualitative research, with good reason (Liamputtong 2013).Using verbal communication and face-to-face conversation as a means to share our experiences and views of the world around us is fundamental to human social life (Serry and Liamputtong 2017).With a strong grounding in the social convention of conversation, then ...
How To Do Qualitative Interviews For Research
If you need 10 interviews, it is a good idea to plan for 15. Likely, a few will cancel, delay, or not produce useful data. 5. Not keeping your golden thread front of mind. We touched on this a little earlier, but it is a key point that should be central to your entire research process.
How to use and assess qualitative research methods
Abstract. This paper aims to provide an overview of the use and assessment of qualitative research methods in the health sciences. Qualitative research can be defined as the study of the nature of phenomena and is especially appropriate for answering questions of why something is (not) observed, assessing complex multi-component interventions ...
Interview Research
Semi-Structured: Semi-Structured Interview. Entry in The SAGE Encyclopedia of Qualitative Research Methodsby Lioness Ayres; Editor: Lisa M. Given The semi-structured interview is a qualitative data collection strategy in which the researcher asks informants a series of predetermined but open-ended questions.The researcher has more control over the topics of the interview than in unstructured ...
Chapter 13: Interviews
What are interviews? An interviewing method is the most commonly used data collection technique in qualitative research. 1 The purpose of an interview is to explore the experiences, understandings, opinions and motivations of research participants. 2 Interviews are conducted one-on-one with the researcher and the participant. Interviews are most appropriate when seeking to understand a ...
How to Carry Out Great Interviews in Qualitative Research
A qualitative research interview is a one-to-one data collection session between a researcher and a participant. Interviews may be carried out face-to-face, over the phone or via video call using a service like Skype or Zoom. There are three main types of qualitative research interview - structured, unstructured or semi-structured.
Conduct Interviews for Qualitative Research
Qualitative research interviews are depth interviews. They elicit detailed feedback from your leads and customers. Unstructured interviews reveal why people react in a certain way or make certain decisions. According to The Hartford, qualitative research provides an anecdotal look into your business. That provides an important form of data.
The Qualitative Research Interview: Participants' Responsive
As early as the 1980s, qualitative researchers demonstrated sensitivity to the impact of research interviews on participants (Cowles, 1988; Munhall, 1988).Reacting to the hegemony of standardized measures that were thought to "squelch or deform the localized and personal knowledge of research participants" (Gergen, 2001, p. 21), researchers focused on learning about people's often deeply ...
The qualitative research interview
In this article we briefly review the more common qualitative interview methods and then focus on the widely used individual face-to-face in-depth interview, which seeks to foster learning about individual experiences and perspectives on a given set of issues. We discuss methods for conducting in-de …
Twelve tips for conducting qualitative research interviews
Summary. The qualitative research interview is a powerful data-collection tool which affords researchers in medical education opportunities to explore unknown areas of education and practice within medicine. This paper articulates 12 tips for consideration when conducting qualitative research interviews, and outlines the qualitative research ...
Planning Qualitative Research: Design and Decision Making for New
While many books and articles guide various qualitative research methods and analyses, there is currently no concise resource that explains and differentiates among the most common qualitative approaches. We believe novice qualitative researchers, students planning the design of a qualitative study or taking an introductory qualitative research course, and faculty teaching such courses can ...
Qualitative Interview: What it is & How to conduct one
Qualitative interviews usually involve follow-up questions and are conducted in a conversation or discussion format. A qualitative interview is a more personal form of research agenda compared to general questionnaires or focused group studies. Such formats often include open-ended and follow-up questions. LEARN ABOUT: Behavioral Research.
Getting more out of interviews. Understanding interviewees' accounts in
We therefore propose additional interpretative steps to account for the dynamic in the interview setting and reconstruct the formative principles shaping the interview content. ... The interview society and the irresistible rise of the (poorly analyzed) interview. Qualitative Research 17(2): 144-158. Crossref. ISI. Google Scholar. Weber M ...
Qualitative Research: Getting Started
Qualitative research was historically employed in fields such as sociology, ... research question, participants, and settings. The method is the way you carry out your research within the paradigm of quantitative or qualitative research. ... Interviews. Patton 12 has described an interview as "open-ended questions and probes yielding in-depth ...
What Is Qualitative Research?
Qualitative research methods. Each of the research approaches involve using one or more data collection methods.These are some of the most common qualitative methods: Observations: recording what you have seen, heard, or encountered in detailed field notes. Interviews: personally asking people questions in one-on-one conversations. Focus groups: asking questions and generating discussion among ...
Choose a Setting for Qualitative Research Interviews
Choosing the Right Setting for a Qualitative Research Interview. Updated on: October 2, 2023. Tweet. ... Some people are comfortable being interviewed at home, others prefer the outdoors or a telephonic interview. Set up the recording gear before the interview. Beginning on schedule is important. So connect any DVRs/cameras, plug in external ...
Going Beyond Adaptation: An Integrative Review and Ethical
For example, the book The Qualitative Research Interview (Boutin, 2018, free translation from French) has only one section in Chapter 4 about interviewing children, and it covers limited concepts such as children's characteristics, relational and contextual aspects, necessary adaptations, and interview settings (pp. 84-87).
'It's Powerful' The impact of involving children and young people in
We involved VET students in the data analysis and interpretation phase by forming a young person advisory group. The data analysis of the interviews analysed by the VET students revealed four distinct themes: 1. Learnt new knowledge. 2. Learnt to collaborate. 3. Learnt to listen. 4. Assessment of th …
What is Qualitative in Qualitative Research
Qualitative research involves the studied use and collection of a variety of empirical materials - case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts - that describe routine and problematic moments and meanings in individuals' lives.
Behavioral Sciences
Thus, this research explores experiences of parents facing perinatal loss in 2020-2021, further focusing on the pandemic's impact. Using a mixed-methods design with self-reports and qualitative interviews, this paper presents results from the quantitative protocol, involving an update and follow-up of a previous study.

How to conduct qualitative interviews (tips and best practices)

1. Before the interview

2. During the interview

3. After the interview

Explain the purpose of the study

Create a comfortable environment

Build rapport

Use open-ended questions

Listen attentively

Avoid judgment

Offer breaks

1. Transcription

2. Data reduction

4. Categorization

5. Interpretation

6. Comparison

7. Triangulation

8. Synthesis

Use transcription software

Listen carefully

Use appropriate formatting

Edit for clarity

Proofread and edit

Use timestamps

Subjectivity and personal biases

Small sample size

Data quality

Socially desirable responses

Time-consuming

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Introduction

Experimentation

Research design

Study design

Data collection

Topic guide

Optimizing the interview

Ethics and reflexivity

Ethical considerations prior to interview

Box 1 Mapping potential forms of harm

Ethical considerations post-interview

Reflexivity and positionality

Box 2 Aspects to reflect on reflexively

Preparing data

Box 3 Excerpt of interview transcript (from Teeger 24 )

From data to codes

From coding to analysis and writing

Applications

Nationalism and ethnicity

Education and inequality

The welfare state

Reproducibility and data deposition

Box 4 An example of grounding interpretations in data (from Rao 34 )

Limitations and optimizations

Breadth versus depth of insight

Naturalistic or artificial interviews

Dynamism and replicability

Accessing the private and personal

Collaborating and mixing

Digital innovations and challenges

The next 5–10 years

Acknowledgements

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